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Dissertations / Theses on the topic 'Hierarchical search'
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Xu, Xin. "Interactive hierarchical generate and test search." Thesis, University of Ottawa (Canada), 1991. http://hdl.handle.net/10393/7934.
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Most of the search methods used in AI are inflexible. Interactive search is a new kind of search in which the search system can communicate and cooperate with external agents. There are two kinds of agents: human agents and non-human agents. Through interaction with human agents (man-machine interaction), the search system can make use of the human talent of judging the quality of a solution. Through interaction with non-human agents (machine-machine interaction), the search system can automatically exploit knowledge from its environment. An interactive search system has the ability to take advice from external agents. The ordinary non-interactive search models are the special instances of interactive search when the advice sequences are empty. We are investigating a particular kind of Interactive Search, IHGT (Interactive Hierarchical Generate and Test) search, which is established by introducing interactive ability into HGT (Hierarchical Generate and Test) search. To make HGT search interactive, we created an editor called GE (Generator Editor). GE was implemented in Prolog. GE is a bottom level language shell outside the HGT search model which translates advice into dynamic changes of all the three search factors. (Abstract shortened by UMI.)
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Shenoy, U. Nagaraj. "Automatic Data Partitioning By Hierarchical Genetic Search." Thesis, Indian Institute of Science, 1996. http://hdl.handle.net/2005/172.
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CDACThe introduction of languages like High Performance Fortran (HPF) which allow the programmer to indicate how the arrays used in the program have to be distributed across the local memories of a multi-computer has not completely unburdened the parallel programmer from the intricacies of these architectures. In order to tap the full potential of these architectures, the compiler has to perform this crucial task of data partitioning automatically. This would not only unburden the programmer but would make the programs more efficient since the compiler can be made more intelligent to take care of the architectural nuances. The topic of this thesis namely the automatic data partitioning deals with finding the best data partition for the various arrays used in the entire program in such a way that the cost of execution of the entire program is minimized. The compiler could resort to runtime redistribution of the arrays at various points in the program if found profitable. Several aspects of this problem have been proven to be NP-complete. Other researchers have suggested heuristic solutions to solve this problem. In this thesis we propose a genetic algorithm namely the Hierarchical Genetic Search algorithm to solve this problem.
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Normore, Lorraine Dombrowski. "Strategies in searching hierarchical data structures /." The Ohio State University, 1986. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487265143147771.
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Manabe, Tomohiro. "Web Search Based on Hierarchical Heading-Block Structure Analysis." 京都大学 (Kyoto University), 2016. http://hdl.handle.net/2433/215681.
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The contents of Section 2.2 and Chapter 4 first appeared in proceedings of the 12th International Conference on Web Information Systems and Technologies, 2016 (www.webist.org). The contents of Section 2.3 and Chapter 5 first appeared in DBSJ Journal, vol. 14, article no. 2, March 2016. The contents of Section 2.5 and Chapter 7 first appeared in proceedings of the 11th Asia Information Retrieval Societies Conference, Lecture Notes in Computer Science, vol. 9460, pp. 188-200, 2015 (The final publication is available at link.springer.com).Kyoto University (京都大学)
0048
新制・課程博士
博士(情報学)
甲第19854号
情博第605号
新制||情||105(附属図書館)
32890
京都大学大学院情報学研究科社会情報学専攻
(主査)教授 田島 敬史, 教授 田中 克己, 教授 吉川 正俊
学位規則第4条第1項該当
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Dickinson, Anthony R. "Hierarchical organisation in serial search tasks by Cebus apella monkeys." Thesis, University of Edinburgh, 1998. http://hdl.handle.net/1842/21198.
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The thesis reports the first demonstration of two-level hierarchical and linear organisation in six monkeys (Cebus apella). In behaviours elaborated over a four-year period, the hypothesis tested (McGonigle and Chalmers, 1992) was that progressive increases in task difficulty would be compensated by data reducing, economic, organisational structures. Novel touch-screen based procedures required the seriation and search of each item in a test set which, when increased in size, lead to geometrical increases in difficulty. Whilst on one scenario the subject should begin to fail as the task increases in difficulty, the performance of all subjects has shown progressive adaptation to such task requirements. This indicates an underlying dynamic process consistent with the operating hypothesis that cognitive organisation, both linear and hierarchical, are emergent responses motivated by a need for cognitive economy.
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Roshani, Asra. "Unsupervised segmentation of sequences using harmony search and hierarchical clustering techniques." Master's thesis, Université Laval, 2014. http://hdl.handle.net/20.500.11794/25350.
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Dans le contexte de traitement automatique du langage naturel, les données le plus souvent sont présentées comme une longue séquence de caractères discrets. Donc, l'identification d'un modèle intéressant dans la longue séquence peut être une tâche difficile. En conséquence, la segmentation automatique de données serait extrêmement utile pour extraire les sous-séquences et les morceaux significatifs à partir d'une longue séquence de données. La segmentation de données est l'une des étapes de prétraitement les plus importantes dans plusieurs tâches de traitement du langage naturel. La segmentation de mots est considérée comme la tâche de trouver des morceaux significatifs dans le corpus de textes. L'objectif principal de cette étude est de présenter une technique de segmentation hiérarchique non supervisée en utilisant l'algorithme de recherche d'harmonie (Harmony Search algorithm) qui est une approche d'optimisation méta-heuristique. Dans la technique proposée, la tâche de segmentation de mots est réalisée à l'aide d'une recherche d'harmonie binaire (Binary Harmony search) qui une forme particulière de l'algorithme de recherche d'harmonie. La construction et la formation de modèles de langue sont accomplies par un lexique hiérarchique et un algorithme de Baum-Welch. De plus, pour améliorer la performance et la convergence de la recherche de l'harmonie binaire, quelques modifications innovantes sont appliquées. En général, cette étude présente un algorithme de segmentation de mots hiérarchique non supervisée basée sur une méthode recherche de l'harmonie et examine toutes les questions relatives y compris: la segmentation de mots représentées en format binaire, l'harmonie binaire, l'amélioration de la procédure de l'ajustement du lancement, la définition de la fonction objective en recherche d'harmonie et la politique de pénalité. La performance de l'algorithme est évaluée selon la précision de la segmentation, le rappel, la F-mesure et le temps d'exécution de l'algorithme. Une partie du corpus Moby Dick est utilisée comme étude de cas. Nos expérimentations montrent que l'approche de segmentation basée sur une recherche d'harmonie fournit plusieurs de bons segments, mais qu'il nécessite un long temps d'exécution.In the context of natural language processing, data is presented most of the time as a long sequence of discrete characters. Therefore, identifying interesting patterns within the long sequence can be a challenging task. Consequently, automatic segmentation of data would be extremely useful to extract the meaningful sub-sequences and chunks from a long data sequence. Segmentation of raw data is one of the most important preprocessing steps in many natural language processing tasks. Word segmentation is considered as the task of finding meaningful chunks, i.e. words, within a text corpus. The main objective of this study is to present an unsupervised hierarchical segmentation technique using Harmony Search algorithm which is a meta-heuristic optimization approach. In the proposed technique, the word segmentation task is performed using a Binary Harmony Search (a special form of Harmony Search). The language model construction and training are accomplished using a hierarchical lexicon and Baum-welch algorithm. Moreover, to improve the performance and convergence of the Binary Harmony Search, some innovative modifications are applied. In general, this study introduces an unsupervised hierarchical word segmentation algorithm based on Harmony Search approach and investigates the following related issues: word segmentation mapping to binary format, Binary Harmony Search, pitch adjustment procedure improvement, Harmony Search objective function definition, and penalty policy. The performance of the algorithm is valuated using segmentation precision, recall, F-measure and the algorithm run time when applied to the part of famous Moby Dick story as the case study. Our experiments reveal that the segmentation approach based on Harmony Search provides significantly good segments, while it requires significant run time.
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Anguelov, Bobby. "Video game pathfinding and improvements to discrete search on grid-based maps." Diss., University of Pretoria, 2011. http://hdl.handle.net/2263/22940.
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The most basic requirement for any computer controlled game agent in a video game is to be able to successfully navigate the game environment. Pathfinding is an essential component of any agent navigation system. Pathfinding is, at the simplest level, a search technique for finding a route between two points in an environment. The real-time multi-agent nature of video games places extremely tight constraints on the pathfinding problem. This study aims to provide the first complete review of the current state of video game pathfinding both in regards to the graph search algorithms employed as well as the implications of pathfinding within dynamic game environments. Furthermore this thesis presents novel work in the form of a domain specific search algorithm for use on grid-based game maps: the spatial grid A* algorithm which is shown to offer significant improvements over A* within the intended domain. CopyrightDissertation (MSc)--University of Pretoria, 2011.
Computer Science
unrestricted
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Zheng, Li. "Towards Next Generation Vertical Search Engines." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1517.
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As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results.
In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.
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Fang, Qijun. "Model search strategy when P >> N in Bayesian hierarchical setting." View electronic thesis (PDF), 2009. http://dl.uncw.edu/etd/2009-2/fangq/qijunfang.pdf.
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Salomatin, Konstantin. "Large-scale hierarchical optimization for online advertising and wind farm planning." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/337.
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This thesis develops a framework to investigate and design novel optimization methods for two important problems: computational advertising (particularly, sponsored search) and wind farm turbine-layout planning. Whereas very different in specifics, both problems share some common abstractions. The existing solution in sponsored search is based on a greedy pay-per-click auction and is suitable only for advertisers seeking a direct response. It does not apply to advertisers who target certain numbers of clicks in a predefined time period. To address this new challenge, we introduce a unified optimization framework combining pay-per-click auctions and guaranteed delivery in sponsored search. Our new method maximizes the revenue of the search engine, targets a guaranteed number of ad clicks per campaign for advertisers willing to pay a premium, and enables keyword auctions for all others. Results combining revenue to the search engine and click rates for the advertisers show superior performance over strong baselines. The proposed framework is based on linear programming with delayed column generation for computational tractability at scale. We design a game theoretic approach to optimize the strategy for individual advertisers, i.e. to optimize their choices between auctions and guaranteed delivery, and analyze the behavior of the new market formed by our framework. Specifically, we introduce a new method for computing the approximate Nash equilibrium where an exact computation would prove computationally intractable. We rely on approximations of complex utility functions, a combination of simulated annealing and integer linear programming as our principled approach. Wind farm layout optimization is the selection of optimal locations for placement of large wind turbines taking into account factors such as topographical features, prevalent but non-constant wind direction and turbine-wake interference. Existing approaches are deficient in their inability to consider long distance turbine interference, changing wind speed and direction and multiple types of wind turbines in optimization. The dissertation develops an optimization framework based on a scalable divided-and-conquer strategy that enables scalability to real-world wind farm scales taking into account the aforementioned complexities in the optimization process. Essentially the process optimizes in a hierarchical manner at different levels of granularity. This hierarchical decomposition approach to optimization is common to both search-advertisement and wind-farm layout challenges.
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Douglas-Brown, Denise. "In search of syntactic symmetry : on the parallels between clausal and nominal hierarchical structure." Thesis, Durham University, 1996. http://etheses.dur.ac.uk/1461/.
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Zhu, Dengya. "Improving the relevance of search results via search-term disambiguation and ontological filtering." Curtin University of Technology, School of Information Systems, 2007. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=9348.
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With the exponential growth of the Web and the inherent polysemy and synonymy problems of the natural languages, search engines are facing many challenges such as information overload, mismatch of search results, missing relevant documents, poorly organized search results, and mismatch of human mental model of clustering engines. To address these issues, much effort including employing different information retrieval (IR) models, information categorization/clustering, personalization, semantic Web, ontology-based IR, and so on, has been devoted to improve the relevance of search results. The major focus of this study is to dynamically re-organize Web search results under a socially constructed hierarchical knowledge structure, to facilitate information seekers to access and manipulate the retrieved search results, and consequently to improve the relevance of search results.To achieve the above research goal, a special search-browser is developed, and its retrieval effectiveness is evaluated. The hierarchical structure of the Open Directory Project (ODP) is employed as the socially constructed knowledge structure which is represented by the Tree component of Java. Yahoo! Search Web Services API is utilized to obtain search results directly from Yahoo! search engine databases. The Lucene text search engine calculates similarities between each returned search result and the semantic characteristics of each category in the ODP; and thus to assign the search results to the corresponding ODP categories by Majority Voting algorithm. When an interesting category is selected by a user, only search results categorized under the category are presented to the user, and the quality of the search results is consequently improved.
Experiments demonstrate that the proposed approach of this research can improve the precision of Yahoo! search results at the 11 standard recall levels from an average 41.7 per cent to 65.2 per cent; the improvement is as high as 23.5 per cent. This conclusion is verified by comparing the improvements of the P@5 and P@10 of Yahoo! search results and the categorized search results of the special search-browser. The improvement of P@5 and P@10 are 38.3 per cent (85 per cent - 46.7 per cent) and 28 per cent (70 per cent - 42 per cent) respectively. The experiment of this research is well designed and controlled. To minimize the subjectiveness of relevance judgments, in this research five judges (experts) are asked to make their relevance judgments independently, and the final relevance judgment is a combination of the five judges’ judgments. The judges are presented with only search-terms, information needs, and the 50 search results of Yahoo! Search Web Service API. They are asked to make relevance judgments based on the information provided above, there is no categorization information provided.
The first contribution of this research is to use an extracted category-document to represent the semantic characteristics of each of the ODP categories. A category-document is composed of the topic of the category, description of the category, the titles and the brief descriptions of the submitted Web pages under this category. Experimental results demonstrate the category-documents of the ODP can represent the semantic characteristics of the ODP in most cases. Furthermore, for machine learning algorithms, the extracted category-documents can be utilized as training data which otherwise demand much human labor to create to ensure the learning algorithm to be properly trained. The second contribution of this research is the suggestion of the new concepts of relevance judgment convergent degree and relevance judgment divergent degree that are used to measure how well different judges agree with each other when they are asked to judge the relevance of a list of search results. When the relevance judgment convergent degree of a search-term is high, an IR algorithm should obtain a higher precision as well. On the other hand, if the relevance judgment convergent degree is low, or the relevance judgment divergent degree is high, it is arguable to use the data to evaluate the IR algorithm. This intuition is manifested by the experiment of this research. The last contribution of this research is that the developed search-browser is the first IR system (IRS) to utilize the ODP hierarchical structure to categorize and filter search results, to the best of my knowledge.
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Mayorova, Olga Vladislavovna. "Social Capital and Institutional Transition: Regional Context for Network Use in Job Search in Russia, 1985-2001." Diss., The University of Arizona, 2008. http://hdl.handle.net/10150/193995.
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Current research on network use in the labor market focuses primarily on network morphology. In this dissertation, I use hierarchical regression to examine the influence of macro-level context on network use in job search.This study relies on a unique data set that combines individual job history data for years 1985 through 2001 collected by the Survey of Social Dynamics and Migration in Russia (SSMDR) in 40 regions in 2001-2002 and corresponding regional macro-economic data published by Goskomstat, the State Statistical Committee of the Russian Federation.The first question of this study focuses on what accounts for the temporal and regional variation in personal network use in the Russian labor market. I find that, for the post-Soviet period, increase in network use in job search can be attributed to the growth of the private sector: Russian employers are becoming "social capitalists" who take advantage of the resources personal connections can offer. I also find that the chances of finding a new job through personal ties are higher in the regions with larger small business sectors and in the regions with lower economic performance.Next I examine how regional economic performance and unemployment affect workers' chances of getting new jobs in the private sector and in smaller size organizations by means of personal networks. The analysis shows that social networks do lead to employment in the private sector and that this relationship is positively affected by regional economic performance, but not by unemployment rate. I also find here that social ties are likely to lead to new jobs in small organizations, but that this relationship does not vary by region.Finally, I investigate how regional economic performance and unemployment rates affect wages for jobs found through personal networks in the private sector and in small organizations. I find that while the private sector rewards network use, small organizations do not. The relationship between network use and wages does not vary by region. That is, regional economic performance does not have an effect on this relationship.
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Cowlagi, Raghvendra V. "Hierarchical motion planning for autonomous aerial and terrestrial vehicles." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41066.
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Autonomous mobile robots - both aerial and terrestrial vehicles - have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory.
Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle.
Although simple and efficient, such hierarchical separation suffers a serious drawback: the geometric path planner has no information of the kinematic and dynamic constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates altogether the geometric planner by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematic model.
In this thesis, we propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. We show that the proposed motion planning approach offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning. Finally, we propose a multi-resolution implementation of the proposed motion planner, which requires accurate descriptions of the environment and the vehicle only for short-term, local motion planning in the immediate vicinity of the vehicle.
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Watchravesringkan, Kittichai. "A hierarchical model of values, price perception, ongoing search and shopping behaviors: A cross-cultural comparison." Diss., The University of Arizona, 2005. http://hdl.handle.net/10150/280776.
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A considerable degree of cross-cultural research has recognized the impact of cultural values of individualism and collectivism on individuals' consumption behavior. Recently, the impact of international market expansion and modernization may have helped transform values of materialism among Asians. It is evident that values have a hierarchical influence on consumption behavior through higher-order cognition (e.g., perceptions and attitudes). In this study, we argue that materialism, individualism, and collectivism have an impact on consumers' ongoing search and shopping behaviors through consumers' perceived two different roles of price: symbolic and functional. The symbolic role reflects a person's self-enhancement, role position, and self-image, whereas the functional role implies the motivational aspect of an individual's consumption. This current paper is comprised of two studies. In study one, we attempt to establish the overall hierarchical flow of the cultural values of materialism, individualism, and collectivism with regard to consumers' perceived symbolic and functional roles of price, which in turn affect their ongoing search and mall shopping behavior for apparel products based on the combined sample from two cultures, American and Korean. In study two, we focus on establishing a cross-cultural validation of the hierarchical model of values-price perception-ongoing search-shopping behaviors in four countries (the United States, Canada, Thailand, and China). Additionally, study two extends study one by incorporating both horizontal versus vertical individualism and collectivism and the role of the Internet as informational and transactional sources into the hierarchical model. The final sample is comprised of 806 college students. Of these, 192 are Americans, 158 are Canadian, 248 are Thai, and 208 are Chinese. The present findings illustrate that cross-cultural validation using the hierarchical model of values-price perception-ongoing search-shopping behavior is established. However, the underlying constructs explaining such flow differ considerably across cultures. Using a culture (i.e., region) and an individual (i.e., country) level of analysis, we further found that there are differences and similarities related to materialism; as well, the impact of horizontal versus vertical individualism and collectivism and the interrelationships among these constructs are examined. Implications for future theoretical and practitioner research are provided. Limitations and future research directions are also acknowledged.
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Elkawkagy, Mohamed Mohamed Nabil Mohamed Shams Eldeen [Verfasser]. "Hierarchical landmarks - a means to reduce search effort in hybrid planning / Mohamed Mohamed Nabil Mohamed Shams Eldeen Elkawkagy." Ulm : Universität Ulm. Fakultät für Ingenieurwissenschaften und Informatik, 2011. http://d-nb.info/1016716524/34.
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Bolin, Jakob, and Nico Palmroos. "Monte-Carlo Tree Search Used for Fortification in the Game of Risk." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297698.
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The strategy game Risk is a very popular boardgame, requiring little effort to learn but lots of skill to master.The aim of this project is to explore the fortification phase of thegame, where the player’s troops are moved between territories.Our method is based on adapting Monte Carlo tree search(MCTS) to Risk. To improve the troop movements, we proposetwo techniques, hierarchical search and progressive bias. Thesemethods, combined with other extensions of MCTS are thencompared against a baseline player of the game. Our results showthat hierarchical search improved the MCTS agent’s playingpower and the progressive bias have potential to improve theagent but needs further investigation.Strategispelet Risk är ett väldigt populärt brädspel som är lätt att lära sig men svårt att bemästra. Syftet med detta projekt är att utforska spelets befästningsfas, där spelarens trupper flyttas mellan territorier. Vår metod är baserad på en anpassning av Monte Carlo trädsökning (MCTS) till Risk. För att förbättra trupprörelserna föreslår vi två tekniker, ”hierarchical search” och ”progressive bias”. Dessa metoder, i kombination med andra tillägg av MCTS, jämförs sedan mot en standard agent i spelet. Våra resultat visar att hierarchical search förbättrade MCTS agentens spelstyrka och att progressivce bias har möjlighet att förbättra agenten men kräver fortsatt utforskning.
Kandidatexjobb i elektroteknik 2020, KTH, Stockholm
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CASTRO, RENER PEREIRA DE. "STATISTICAL OPTIMIZATION OF SPATIAL HIERARCHICAL STRUCTURES SEARCHS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=11695@1.
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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOREste trabalho surgiu da seguinte observação: os clássicos algoritmos de busca em 2d-tree começam da raiz para acessar dados armazenados nas folhas. Entretanto, como as folhas são os nós mais distantes da raiz, por que começar as buscas pela raiz? Com representações clássicas de 2d-trees, não existe outra forma de acessar uma folha. Existem 2d- trees, porém, que permitem acessar em tempo constante qualquer nó, dado sua posição e seu nível. Para o algoritmo de busca, a posição é conhecida, mas o nível não. Para estimar o nível de um nó qualquer, um método de otimização estatística do custo médio das buscas é proposto. Como os piores custos de busca são obtidos quando se começa da raiz, este método melhora ambos: o consumo de memória pelo uso de 2d-trees que permitem acessar em tempo constante qualquer nó, e o tempo de execução através da otimização proposta.
This work emerged from the following observation: usual search procedures for 2d-trees start from the root to retrieve the data stored at the leaves. But since the leaves are the farthest nodes to the root, why start from the root? With usual 2d-trees representations, there is no other way to access a leaf. However, there exist 2d-trees which allow accessing any node in constant time, given its position in space and its depth in the 2d-tree. Search procedures take the position as an input, but the depth remains unknown. To estimate the depth of an arbitrary node a statistical optimization of the average cost for the search procedures is introduced. Since the highest costs of these algorithms are obtained when starting from the root, this method improves on both, the memory footprint by the use of 2d-trees which allow accessing any node in constant time, and execution time through the proposed optimization.
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Hinz, Joel. "Clustering the Web : Comparing Clustering Methods in Swedish." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-95228.
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Clustering -- automatically sorting -- web search results has been the focus of much attention but is by no means a solved problem, and there is little previous work in Swedish. This thesis studies the performance of three clustering algorithms -- k-means, agglomerative hierarchical clustering, and bisecting k-means -- on a total of 32 corpora, as well as whether clustering web search previews, called snippets, instead of full texts can achieve reasonably decent results. Four internal evaluation metrics are used to assess the data. Results indicate that k-means performs worse than the other two algorithms, and that snippets may be good enough to use in an actual product, although there is ample opportunity for further research on both issues; however, results are inconclusive regarding bisecting k-means vis-à-vis agglomerative hierarchical clustering. Stop word and stemmer usage results are not significant, and appear to not affect the clustering by any considerable magnitude.
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Kamenieva, Iryna. "Research Ontology Data Models for Data and Metadata Exchange Repository." Thesis, Växjö University, School of Mathematics and Systems Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-6351.
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For researches in the field of the data mining and machine learning the necessary condition is an availability of various input data set. Now researchers create the databases of such sets. Examples of the following systems are: The UCI Machine Learning Repository, Data Envelopment Analysis Dataset Repository, XMLData Repository, Frequent Itemset Mining Dataset Repository. Along with above specified statistical repositories, the whole pleiad from simple filestores to specialized repositories can be used by researchers during solution of applied tasks, researches of own algorithms and scientific problems. It would seem, a single complexity for the user will be search and direct understanding of structure of so separated storages of the information. However detailed research of such repositories leads us to comprehension of deeper problems existing in usage of data. In particular a complete mismatch and rigidity of data files structure with SDMX - Statistical Data and Metadata Exchange - standard and structure used by many European organizations, impossibility of preliminary data origination to the concrete applied task, lack of data usage history for those or other scientific and applied tasks.
Now there are lots of methods of data miming, as well as quantities of data stored in various repositories. In repositories there are no methods of DM (data miming) and moreover, methods are not linked to application areas. An essential problem is subject domain link (problem domain), methods of DM and datasets for an appropriate method. Therefore in this work we consider the building problem of ontological models of DM methods, interaction description of methods of data corresponding to them from repositories and intelligent agents allowing the statistical repository user to choose the appropriate method and data corresponding to the solved task. In this work the system structure is offered, the intelligent search agent on ontological model of DM methods considering the personal inquiries of the user is realized.
For implementation of an intelligent data and metadata exchange repository the agent oriented approach has been selected. The model uses the service oriented architecture. Here is used the cross platform programming language Java, multi-agent platform Jadex, database server Oracle Spatial 10g, and also the development environment for ontological models - Protégé Version 3.4.
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ASNAGHI, COSTANZA. "Un'Analisi della Variazione Lessicale Regionale Nell’Inglese di California Attraverso le Ricerche in Rete Limitate per Sito." Doctoral thesis, Università Cattolica del Sacro Cuore, 2013. http://hdl.handle.net/10280/1811.
Full textAbstract:
Lo studio esamina la variazione lessicale regionale in forma scritta nell’inglese standard in California. Attraverso ricerche in rete limitate a 336 siti di giornali online con sede in 270 città in California, vengono raccolti i valori di 45 variabili continue di alternanze lessicali e quindi calcolati come proporzioni. Tecniche statistiche di autocorrelazione spaziale globale e locale analizzano i valori. I risultati delle analisi, riportati in 90 mappe, confermano la distribuzione regionale delle variabili in California. Le 45 variabili lessicali sono poi esaminate con tecniche statistiche multivariate per individuare le relazioni linguistiche tra le città della California esaminate. L’analisi fattoriale, che rappresenta il 50,5% della variazione nei dati, evidenzia tre aree nella distribuzione regionale lessicale: nord/sud, urbano/rurale, e aree centrali e basso meridionali/aree alto meridionali e del nord. L’analisi dei cluster gerarchica distingue inoltre sei regioni dialettali principali in California: quella del Nord, quella di Sacramento-Santa Cruz, quella della San Francisco Bay Area, quella centrale, quella alto meridionale, e quella basso meridionale. Cinque mappe multivariate sono fornite nella tesi. La spiegazione dei risultati si basa sia su modelli di insediamento storico che su una spiegazione socio-culturale, che si riflettono nel linguaggio in California.The study examines regional lexical variation in written Standard California English. The valuesof 45 continuous lexical alternation variables are gathered through site-restricted web searches in 336 online newspaper websites based in 270 locations in California and then calculated as proportions. Statistical techniques analyze global and local spatial autocorrelation values. The results of the analysis, reported in 90 maps, confirm the regional distribution of the variables in California. The 45 lexical variables are then analyzed with multivariate techniques to identify the linguistic relations between the surveyed California cities. Factor analysis, which accounts for 50.5% of the variation in the data, highlights three areas in the regional lexical distribution: north/south, urban/rural, central and lower southern/upper southern and northern areas. The hierarchical cluster analysis also distinguishes six major dialect regions in California: the North dialect region, the Sacramento-Santa Cruz dialect region, the San Francisco Bay Area dialect region, the Central dialect region, the Upper Southerns dialect region, and the Lower Southern dialect region. Five multivariate maps are provided in the thesis. The explanation of the results is based both on historical settlement patterns and on a socio-cultural explanation, which are reflected in the language in California.
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"A probabilistic cooperative-competitive hierarchical search model." 1998. http://library.cuhk.edu.hk/record=b5889641.
Full textAbstract:
by Wong Yin Bun, Terence.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.
Includes bibliographical references (leaves 99-104).
Abstract also in Chinese.
List of Figures --- p.ix
List of Tables --- p.xi
Chapter I --- Preliminary --- p.1
Chapter 1 --- Introduction --- p.2
Chapter 1.1 --- Thesis themes --- p.4
Chapter 1.1.1 --- Dynamical view of landscape --- p.4
Chapter 1.1.2 --- Bottom-up self-feedback algorithm with memory --- p.4
Chapter 1.1.3 --- Cooperation and competition --- p.5
Chapter 1.1.4 --- Contributions to genetic algorithms --- p.5
Chapter 1.2 --- Thesis outline --- p.5
Chapter 1.3 --- Contribution at a glance --- p.6
Chapter 1.3.1 --- Problem --- p.6
Chapter 1.3.2 --- Approach --- p.7
Chapter 1.3.3 --- Contributions --- p.7
Chapter 2 --- Background --- p.8
Chapter 2.1 --- Iterative stochastic searching algorithms --- p.8
Chapter 2.1.1 --- The algorithm --- p.8
Chapter 2.1.2 --- Stochasticity --- p.10
Chapter 2.2 --- Fitness landscapes and its relation to neighborhood --- p.12
Chapter 2.2.1 --- Direct searching --- p.12
Chapter 2.2.2 --- Exploration and exploitation --- p.12
Chapter 2.2.3 --- Fitness landscapes --- p.13
Chapter 2.2.4 --- Neighborhood --- p.16
Chapter 2.3 --- Species formation methods --- p.17
Chapter 2.3.1 --- Crowding methods --- p.17
Chapter 2.3.2 --- Deterministic crowding --- p.18
Chapter 2.3.3 --- Sharing method --- p.18
Chapter 2.3.4 --- Dynamic niching --- p.19
Chapter 2.4 --- Summary --- p.21
Chapter II --- Probabilistic Binary Hierarchical Search --- p.22
Chapter 3 --- The basic algorithm --- p.23
Chapter 3.1 --- Introduction --- p.23
Chapter 3.2 --- Search space reduction with binary hierarchy --- p.25
Chapter 3.3 --- Search space modeling --- p.26
Chapter 3.4 --- The information processing cycle --- p.29
Chapter 3.4.1 --- Local searching agents --- p.29
Chapter 3.4.2 --- Global environment --- p.30
Chapter 3.4.3 --- Cooperative refinement and feedback --- p.33
Chapter 3.5 --- Enhancement features --- p.34
Chapter 3.5.1 --- Fitness scaling --- p.34
Chapter 3.5.2 --- Elitism --- p.35
Chapter 3.6 --- Illustration of the algorithm behavior --- p.36
Chapter 3.6.1 --- Test problem --- p.36
Chapter 3.6.2 --- Performance study --- p.38
Chapter 3.6.3 --- Benchmark tests --- p.45
Chapter 3.7 --- Discussion and analysis --- p.45
Chapter 3.7.1 --- Hierarchy of partitions --- p.45
Chapter 3.7.2 --- Availability of global information --- p.47
Chapter 3.7.3 --- Adaptation --- p.47
Chapter 3.8 --- Summary --- p.48
Chapter III --- Cooperation and Competition --- p.50
Chapter 4 --- High-dimensionality --- p.51
Chapter 4.1 --- Introduction --- p.51
Chapter 4.1.1 --- The challenge of high-dimensionality --- p.51
Chapter 4.1.2 --- Cooperation - A solution to high-dimensionality --- p.52
Chapter 4.2 --- Probabilistic Cooperative Binary Hierarchical Search --- p.52
Chapter 4.2.1 --- Decoupling --- p.52
Chapter 4.2.2 --- Cooperative fitness --- p.53
Chapter 4.2.3 --- The cooperative model --- p.54
Chapter 4.3 --- Empirical performance study --- p.56
Chapter 4.3.1 --- pBHS versus pcBHS --- p.56
Chapter 4.3.2 --- Scaling behavior of pcBHS --- p.60
Chapter 4.3.3 --- Benchmark test --- p.62
Chapter 4.4 --- Summary --- p.63
Chapter 5 --- Deception --- p.65
Chapter 5.1 --- Introduction --- p.65
Chapter 5.1.1 --- The challenge of deceptiveness --- p.65
Chapter 5.1.2 --- Competition: A solution to deception --- p.67
Chapter 5.2 --- Probabilistic cooperative-competitive binary hierarchical search --- p.67
Chapter 5.2.1 --- Overview --- p.68
Chapter 5.2.2 --- The cooperative-competitive model --- p.68
Chapter 5.3 --- Empirical performance study --- p.70
Chapter 5.3.1 --- Goldberg's deceptive function --- p.70
Chapter 5.3.2 --- "Shekel family - S5, S7, and S10" --- p.73
Chapter 5.4 --- Summary --- p.74
Chapter IV --- Finale --- p.78
Chapter 6 --- A new genetic operator --- p.79
Chapter 6.1 --- Introduction --- p.79
Chapter 6.2 --- Variants of the integration --- p.80
Chapter 6.2.1 --- Fixed-fraction-of-all --- p.83
Chapter 6.2.2 --- Fixed-fraction-of-best --- p.83
Chapter 6.2.3 --- Best-from-both --- p.84
Chapter 6.3 --- Empricial performance study --- p.84
Chapter 6.4 --- Summary --- p.88
Chapter 7 --- Conclusion and Future work --- p.89
Chapter A --- The pBHS Algorithm --- p.91
Chapter A.1 --- Overview --- p.91
Chapter A.2 --- Details --- p.91
Chapter B --- Test problems --- p.96
Bibliography --- p.99
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Wu, Chia-lu, and 巫佳錄. "Construct Hierarchical User Search Goals by Using Search Result Snippets to Improve Web Search Performance." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/09524627498980122130.
Full textAbstract:
碩士國立成功大學
資訊工程學系碩博士班
96
The invention of the Internet brings much convenience for human community. There are more and more useful and divers data on the web. However the length of submitted queries by users are usually no more than 3 words, so that a lot of search result snippets returned by search engines cause users to spend much time in browsing them one by one. In fact, we consider that users will have potential search goals in their mind when they submit queries to search engines, and there are three classes of user search goals, including resource-seeking, informational, and navigational. In this paper, we extract text labels that matched the user search goal from search result snippets returned by Google, and expect to enhance search performance. We use the most popular techniques SVM to deal with the classification of snippet, and detect text labels which matched user search goals and semantic relevance which improved search goals automatically from each class of snippets, so that the user search goals with higher semantic relevance can get higher ranking, and classifies each type of user search goals in depth by our proposed Hierarchical User Search Goal Model. Finally, we improve search performance by proposing a User-Search-Goal-Base Search Model (USGBSM). The major contribution of this paper is that we further classifies three classes of user search goals in depth based on some new factors like query term, user search goal to enhance search performance thus users can find the snippet that they want to click more quickly.
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Kelly, Stephen. "ON DEVELOPMENTAL VARIATION IN HIERARCHICAL SYMBIOTIC POLICY SEARCH." 2012. http://hdl.handle.net/10222/15376.
Full textAbstract:
A hierarchical symbiotic framework for policy search with genetic programming (GP)
is evaluated in two control-style temporal sequence learning domains. The symbiotic
formulation assumes each policy takes the form of a cooperative team between multiple
symbiont programs. An initial cycle of evolution establishes a diverse range of
host behaviours with limited capability. The second cycle uses these initial policies
as meta actions for reuse by symbiont programs. The relationship between development and ecology is explored by explicitly altering the interaction between learning agent and environment at fixed points throughout evolution. In both task domains, this developmental diversity significantly improves performance. Specifically, ecologies designed to promote good specialists in the first developmental phase and then good generalists result in much stronger organisms from the perspective of generalization ability and efficiency. Conversely, when there is no diversity in the interaction between task environment and policy learner, the resulting hierarchy is not as robust
or general.
The relative contribution from each cycle of evolution in the resulting hierarchical
policies is measured from the perspective of multi-level selection. These multi-level
policies are shown to be significantly better than the sum of contributing meta actions.
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Fan, Kai-Ting, and 范凱婷. "A Hierarchical-Search Block Matching Motion Estimation Processor." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/14184443855276779465.
Full textAbstract:
碩士國立交通大學
電子工程學系
85
In this thesis, a VLSI architecture for motion estimation baed on a hierarchical-search block matching algorithm (HSBMA) is developed. The proposed architecture can deal with the full- search block matching algorithm(FSBMA) as well. To meet the real-time requirement of MPEG-2 MP@ML, parallelprocessing is in great demand. Adopting semi-systolic array (SSA) architecture, 100% hardware efficiency can be achieved within processingelement (PE) array. This proposed architecture mainly consists of fiveunits, namely control unit, memory bank unit, 2-D processing element array,summation unit and comparison unit. The key feature of this design is that the maximum possible reuse of overlapped search area pixels is considered,which can reduce the bandwidth of the frame memory interface. Also, scalabledesign is included. By cascading several chips, we can process the referenceblock with different sizes. Based on 0.6um Compass library and TSMC 0.6um SPDM process technology, clock up to 71.4 MHz can be achieved. The resultimplies that this chip can meet the real time requirement of MPEG-2 MP@MLencoding.
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Lin, Jia-Jeng, and 林家正. "Search Engine with Hierarchical Structures for Incomplete Queries." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/pyss2u.
Full textAbstract:
碩士國立臺灣科技大學
資訊工程系
94
In recent decades, Internet grows up quickly and provides very much information. It’s hard for us to find useful information because information is increasing rapidly. There are limited information on Internet before, so we can find information with few URL. However, the information that we can find are limited. Until now, the information on the Internet is so much that it is impossible to use few URL to present these information. Furthermore, users couldn’t remember too much URL. As a result, users need search engine. We can find the information we needed quickly with search engine. ”Adaptive Search Engine for Incomplete Queries” is the search engine designed for incomplete queries. It can observe the users’ behaviors and find what kind of data users want, then return these data to users to save users’ search time. But this kind of search engine have some problems. First, there must be positive data in initial pages, or search engine will not work.Second, it is sensitive to ”noise”. If users didn’t use it well, it will return bad results. Our research use ”clustering” to improve the system. We increase the probability that the positive data appear in initial pages, and we construct the hierarchical structure with clustering. With the property of the hierarchical structure, we can reduce the range of query and increase the recall rate.
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李忠耕. "Hierarchical Bitmap Search for Non-Fixed Transform-Based Vector Quantization." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/06669171169842531000.
Full textAbstract:
碩士國立成功大學
電機工程學系
85
In recent years, vector quantization (VQ) and transform coding have been treated as the most efficient techniques for image compression. The combinations of vector quantization and transformation techniques, including discrete cosine transform VQ, optimal vector transform VQ, and singular value decomposition VQ, achieve better image quality at the expense of computation complexity. In this thesis, we introduce a hierarchical bitmap search method to reduce their computation loads. All the transformations involved with the bitmaps, even for the multiplicationsk, can be performed by simple binary adders. Especially, the singular value decomposition VQ (SVD- VQ) with the proposed bitmap search method can dramatically reduce the computational complexity. In order to avoid the blind deletion problem in the bitmap search method, we further propose a dynamic bitmap search method to reduce the computation and increase the image quality. The simulations show that the dynamic bitmap search method reduces the computation to about one fifth of the original SVD- VQ required, however, achieves invisible distortion in the reconstructed images.
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Yang, Wun-Chih, and 楊文馳. "A Hierarchical Content Search Engine Based on Unstructured P2P Topology." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/20282067281490922915.
Full textAbstract:
碩士國立中正大學
資訊管理所
96
Peer-to-Peer (P2P) networks are useful and have applied to many fields. In order to quickly retrieve resources on a P2P network, a hierarchical search engine based, on three proposals: NICE protocol, parallel crawler, and distributed PageRank, is proposed. In our method, tasks of document fetching and indexing are distributed to nodes, and these nodes are organized into a hierarchical architecture. Since documents and their indexes are stored locally among nodes, updates on these documents are relatively. In addition, executing queries using the hierarchy can improve search efficiency. Through simulations, we find that our method can perform better than centralized method and flooding method. Also, we can have acceptable precision rate. By adapting several distributed techniques, we can construct a search engine with easier maintenances and higher usability.
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Sun, Chjen-Cheng, and 孫建成. "A hierarchical clustering system to enhance personalized web-snippet search." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/k6m789.
Full textAbstract:
碩士國立中央大學
資訊管理研究所
94
This paper provides a hierarchical web-snippet clustering system with the personalized ability on search engines. According to the user’s query string, the system collects snippets and formulates the corresponding browsing hierarchy to describe contents of snippets. In the browsing hierarchy, every snippet is clustered into fit clusters and the concept of every cluster is described by its label. At the last phase, the system sorts all snippets and labels according to the user’s preferences in the user profile, and outputs the personalized browsing hierarchy. The system applies lexical affinity to extract labels. By using statistical measures the system can extract related but interrupted words as labels. Thus, more flexible forms of labels can be used and as the experiment shows, the system can count label frequency more precisely. In the aspect of building the browsing hierarchy, our research provides an algorithm that extends the DisCover algorithm and can produce a browsing hierarchy without redundancy according to label dispersion. The algorithm selects son labels in greedy way and evaluates every candidate son label against four factors - document coverage、sibling node distinctiveness、redundancy、and compactness. As the experiment shows, the algorithm avoids producing redundancy. In the aspect of constructing the user profile, the system uses a reference ontology and documents which describe user’s preference to build the directory-like user profile. At the online phase, the system sorts snippets and labels according to their importance. The importance of one snippet is computed from weights and similarities of related directories in the user profile. The importance of one label is weighted according to the label frequency, the label depth, and related snippets on the node. As the experiments shows, the system can assist the user in searching information by sorting snippets. The effectiveness of our system includes discovering thematic relationships among snippets and assisting in searching wanted information. The contribution of our research is twofold: 1. To provide a hierarchical document clustering algorithm which can be used to build the browsing hierarchy without redundancy. 2. To apply a profile-based classifier to the web-snippet clustering system to produce the personalized browsing hierarchy.
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Swartz, Michael D. "Stochastic search gene suggestion: Hierarchical Bayesian model selection meets gene mapping." Thesis, 2004. http://hdl.handle.net/1911/18711.
Full textAbstract:
This dissertation introduces a novel approach for addressing the complexities of mapping a complex disease by adjusting a Bayesian Model Selection method. Mapping the genes for a complex disease, such as Rheumatoid Arthritis, involves finding multiple genetic loci that may contribute to the onset of the disease. Pairwise testing of the loci leads to the problem of multiple testing. To avoid multiple tests, one can look at haplotypes, or linear sets of loci, but this results in a contingency table with sparse counts, especially when using marker loci with multiple alleles. In order to jointly consider all loci in the problem, we applied a Hierarchical Bayesian Model Selection method to a conditional logistic regression model used in gene mapping. We chose Stochastic Search Variable Selection for its use of latent indicator variables to indicate those covariates, in this case genes, important to the model. We extended the latent variable structure to mirror genetics through a latent allele indicator conditional on a latent locus indicator. We also examined using a prior correlation structure on the allele coefficients that mirrors linkage disequilibrium, a between-locus genetic correlation structure. Ultimately, we ruled out the usefulness of a dependent covariance structure on the prior for allele main effects, but we developed a preliminary method of fitting a positive definite matrix to data based on adjusting the kriging covariance functions commonly used in geostatistics or spatial statistics. We developed a Metropolis-within-Gibbs algorithm to sample our gene suggestion posterior, and evaluated the algorithm's performance on simulated data and completed the research with application to real data, searching for genes associated with Rheumatoid Arthritis. On simulated data, we found that our method successfully recognized disease loci and nondisease loci. Despite complications when analyzing the real data, our method did indicate the genes more strongly associated with Rheumatoid Arthritis.
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何俊岳. "= Hierarchical search and vector smooth in motion estimation for interframe coding." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/63540525625861082919.
Full text
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黃淑華. "Designed hierarchical semantic categorizaiton for the knowledge management via search engine." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/45589468236681650182.
Full textAbstract:
碩士國立中正大學
電機工程研究所
92
With the huge amount of information available on the World Wide Web, Web servers provide a fertile ground for information searches. The Problem that knowledge workers face today is not lack of information any more. Instead, they are in the situation of information overload. People can not quickly and efficiently find out the wanted information among such huge data. Therefore a lots of information technology were still on developed. The traditionally search technology is by understanding the document experts assign specific categories to the document. However, it wastes a lot of resources and has no economic benefits. Therefore, an new automatic text classifier which can help classification process is demand. Inform ion retrieval is aimed at retrieving information that might be useful or relevant to the user. In this paper we research the mutual semantic relationship between terms via term concept. We collect Chinese synonyms for building a synonyms thesaurus, and make use of automatic text classifier subsystem. Keyword constructs a conceptual space or knowledge space by using semantic matrices. Through the idea of conceptual space and semantic network, we expect that traditional information retrieval will be evolved into knowledge retrieval. We apply structure information from XML structure in database.
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Liu, Ssu-Wei, and 劉思微. "Efficient Search Using Hierarchical Clustering in Mobile Peer-to-Peer Networks." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/95384620286018945621.
Full textAbstract:
碩士輔仁大學
資訊工程學系
95
With the quick advancement of both the ad hoc network technology and peer to peer technology, there have been are applications slowly emerging which try to combine those two aspects in the same existing network. It is important to find a suitable method for it. A distributed peer-to-peer network architecture without network client and server seems best suited for execution on a mobile ad hoc network. However, mobile peers suffer from some problems such as limited power capacity and dynamic topology change caused by the mobility of nodes. In this paper, we proposed a hierarchical clustering mechanism for mobile peers to do effective file sharing and management that provided a good performance in a mobile environment. We mapped the overlay network directly to the physical network, and use the Content-Addressable Network (CAN) architecture to do adaptive topology adjustment. Empty blocks were periodically detected and covered by nodes in a neighboring block to keep the system stabilized. Simulation results showed that the hierarchical clustering method could achieve a good performance in mobile peer-to-peer networks.
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Yang, Chao-Hsiang, and 楊朝翔. "A Fast Keyword Search Structured P2P Network with Hierarchical Resource Classification." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/3theu8.
Full textAbstract:
碩士朝陽科技大學
資訊工程系碩士班
93
Nowadays, people became more rely to internet due to the rapid growth of internet. Users need to access to specify servers to search for required services or documents before obtain the resources from the providing server. This method was the common centralized architecture in obtaining resources. However, there are several potential drawbacks of centralized architecture like expanding problems, extra costs, vulnerable to attack and reliability problems. Hence, the proposed of peer-to-peer computing was well discussed and pay attention by everyone. In peer-to-peer networks, there are direct change of resources and documents between users without the access to centralized server. Users can access to desired resources in anywhere and anytime. Although structured peer-to-peer networks is able to provide rapid search of complete file name, however, it is unable to provide rapid search in keyword searching. Although there is a great improvement in keyword searching for several existed methods, however, a keyword lookup table need to be build before the searching process. Moreover, existed files may not be found in the searching process. Hence, we proposed a resource classification mechanism with hierarchical architecture in this paper. Each of the nodes in this architecture no needs to record the info of classification except the leader of each classification which only needs to record the classification info of the next level. Hence, the proposed method can increase the searching performance without increase the number of nodes and additional burden of node. Moreover, existed files may be found accurately in the searching process. In addition, users are classified into certain group with the same interests due to the specify interests of each user. So, users with the same interests are able to interchange resources within the same network. From the experiments, we found that the proposed hierarchical classification architecture not only reduce the searching time of traditional peer-to-peer structure, but also provide the accurate keyword searching rapidly.
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Liu, Kaihua. "Query on Knowledge Graphs with Hierarchical Relationships." 2017. https://scholarworks.umass.edu/masters_theses_2/560.
Full textAbstract:
The dramatic popularity of graph database has resulted in a growing interest in graph queries. Two major topics are included in graph queries. One is based on structural relationship to find meaningful results, such as subgraph pattern match and shortest-path query. The other one focuses on semantic-based query to find question answering from knowledge bases. However, most of these queries take knowledge graphs as flat forms and use only normal relationship to mine these graphs, which may lead to mistakes in the query results. In this thesis, we find hierarchical relationship in the knowledge on their semantic relations and make use of hierarchical relationship to query on knowledge graphs; and then we propose a meaningful query and its corresponding efficient query algorithm to get top-k answers on hierarchical knowledge graphs. We also design algorithms on distributed frameworks, which can improve its performance. To demonstrate the effectiveness and the efficiency of our algorithms, we use CISCO related products information that we crawled from official websites to do experiments on distributed frameworks.
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Hsiao, Hsin-Wei, and 蕭新維. "An Entropy-Based Hierarchical Search Result Clustering Method by Utilizing Augmented Information." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/22828825352958479082.
Full textAbstract:
碩士國立成功大學
資訊工程學系碩博士班
95
Because of the improvement of the technology of search engines, and the massively increase of the number of web pages, the results returned by the search engines are always mixed and disordered. Especially for the queries with multiple topics, the mixed and disorderly situation of the search results would be more obvious. The technology of clustering search results with different topics has therefore been extensively developed. For traditional clustering methods, some researchers clustered the document sets using the similarity between two or more documents, or exploited machine learning clustering manner training some documents to get the cluster rules. However, the structure between web pages and general documents are not always the same. It can not confirm that the technologies with good performance on general documents clustering always perform well on the web pages clustering. The search engines can return information of several hundred to thousand of the pages’ titles, snippets and URLs. Almost all of the technologies about search result clustering must attain further information from the contents of the returned lists. Besides, the efficiency issue is also crucial for the clustering of web pages. In web pages clustering it can not use the same technology of analyzing all the contents to calculate its cluster as general document clustering. Supposing that we apply the method of document clustering on web pages clustering, it might waste a lot of time to get the clustered results. Long execution time is not permitted for a real-time clustering system. For this reason, more efficient methods must be developed to conquer these issues. In this paper we propose some methods with better efficiency that will conquer these issues. We improve one of the previous technologies. We utilize and augment information that search engines returned and integrate the augmented information and entropy calculation in the information. We apply several new methods to attain better clustered search results and reduce execution time. From our experiments is also indicate that these methods we proposed would obtain clustered results with high quality.
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Yang, Zhong-Kai, and 楊仲凱. "EEG Source Estimation using Overlapping-Sphere Forward Model and Hierarchical-Search Beamforming." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/69366193387668346426.
Full textAbstract:
碩士國立交通大學
資訊工程系所
93
Brain is the most important and complicated apparatus of human beings. EEG has been widely applied in functional brain studies due to its high temporal resolution and low cost. In this work, we focus on the development of an accurate and efficient EEG forward model as well as the inverse solution for neuronal source estimation from the EEG measurements. Our forward model successfully gains its accuracy by fitting an overlapping sphere for each EEG sensor. The computation of the overlapping sphere requires only the multi-shell geometry, instead of boundary element method, thus the proposed forward model is easy to compute. Based on the proposed forward model, the beamforming technique is applied to calculate the distributed sources in the brain space. We maximize the power contrast between active state and control state of EEG recorded data to improve the accuracy of inverse solution. Hierarchical search in the solution space is applied to save the amount of computation by searching grid point level by level instead of searching the whole brain space. According to our experiments using phantom data and visual-evoked potential data, the proposed forward model and inverse solution can efficiently and accurately estimate the source of brain activation. A quick and reliable source localization technique for EEG is successfully developed which can be applied on applications when MRI is not available, such as fundamental brain research and brain-computer interface.
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Shen, Heng Tao, Yan Feng Shu, and Bei Yu. "Efficient Semantic-based Content Search in P2P Network." 2003. http://hdl.handle.net/1721.1/3858.
Full textAbstract:
Most existing Peer-to-Peer (P2P) systems support only title-based searches and are limited in functionality when compared to today’s search engines. In this paper, we present the design of a distributed P2P information sharing system that supports semantic-based content searches of relevant documents. First, we propose a general and extensible framework for searching similar documents in P2P network. The framework is based on the novel concept of Hierarchical Summary Structure. Second, based on the framework, we develop our efficient document searching system, by effectively summarizing and maintaining all documents within the network with different granularity. Finally, an experimental study is conducted on a real P2P prototype, and a large-scale network is further simulated. The results show the effectiveness, efficiency and scalability of the proposed system.Singapore-MIT Alliance (SMA)
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Shongwe, Nonhlanhla, and 熊薇. "A Multi-level Hierarchical Index Structure for Supporting Efficient Similarity Search of Tagsets." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/88829320408607936394.
Full textAbstract:
碩士國立臺灣師範大學
資訊工程研究所
99
In this thesis, we propose a multi-level hierarchical index structure to support efficient similarity search for tagsets. The proposed method is designed based on a previous method which supports similarity search in transaction databases with a two-level bounding mechanism. Similar to the previous method, the tagsets are incrementally grouped into clusters. However, a cluster may have sub-clusters in our approach. The tagsets in a leaf-cluster are grouped into batches. Three different thresholds are used to control the degree of similarity at each level of the index structure. Furthermore, we require the tagsets in the same cluster containing at least one common tag to prevent from grouping unrelated tagsets into a cluster. The experimental results show that the proposed multi-level hierarchical index structure provides better performance on execution time of searching than both the proposed method and the naïve method significantly. Besides, with the assistant of an inverted list of clusters, the execution time of the proposed method for deletion and updating is also much better than the other two methods.
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Lin, Chih-Lu, and 林致祿. "Query Result Distillation by Hierarchical Clustering and Result Aggregation on Multiple Search Engines." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/89589171792821861918.
Full textAbstract:
碩士國立成功大學
資訊工程學系碩博士班
94
As the rapid development of the network environment in recent years, we could get more and more Web resources, however some problems happened as followed, e.g., Lacking of the effective method of finding the Web resources. This problem is solved as the birth of the search engines, but there are some other problems and issues needed to be resolved. For some examples that will be mentioned in this paper: (1) for a short query, it is difficult for search engines to understand what users’ goal of the Web search. As a result, search engines are difficult to provide Web resources that are related to users’ search goal. (2) Without the effective method for helping the users, finds their information need among search engines’ enormous indexes. Therefore, this paper will focus on continuing and improving the previous work about clustering, and also try to study the suitability of pre-deciding that whether the query should be clustered or not, in order to avoid additional overheads both the search engines and users.
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Li, Wei-Cheng, and 李韋承. "Toward An Ontology-based Hierarchical Knowledge Map and its Effective Knowledge Search Approach." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/72400371358939852034.
Full textAbstract:
碩士國立成功大學
資訊管理研究所
93
Since the emergence of the Internet, the amount of information has been grown exponentially. Everyone, as a member of knowledge society, is eager for the assistance and advantage brought by information. However, such a huge amount of information not only results in information overloading but also makes traditional information-retrieval tools incapable of dealing with this situation effectively. Thus, a more intelligent information searching and browsing methodology becomes the key issue in digging out useful knowledge in the so-called information smoke. In particular, knowledge map has been shown as a successful tool for tackling the issue. Knowledge maps can take the advantage of computer strength in powerful computation ability, imitate drafting techniques of geography field, compile innumerous data and useful information and then demonstrate the implicit relationship existing the knowledge objects in a visual map. In addition, it provides a whole picture for knowledge works when browsing so that they can benefit from the knowledge sharing and distribution. Moreover, a tree-like hierarchy can help them understand how the architecture of knowledge documents is set instantly in a general view point or how superfluous knowledge maps can be folded up. In this project, we will propose a new methodology of constructing a hierarchical knowledge map which mainly involves ontology-guided feature extraction, conceptual relationship construction by the hierarchical growing self-organizing map algorithm, visualization of the implicit semantic relationships The effectiveness and efficiency the proposed methodology will be justified by performing experiments on real-world applications.
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Po-Hung, Chen, and 陳柏宏. "A SUBSAMPLING HIERARCHICAL SEARCH ALGORITHM FOR FAST BLOCK MOTION ESTIMATION AND IT'S VLSI ARCHITECTURE." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/56652623777472299686.
Full textAbstract:
碩士大同工學院
電機工程研究所
86
Due to the limitation of transmission bandwidth, low-bit rate motionvideo coding and transmitting for integrated service digital networks (ISDN) and high definition television (HDTV) systems has an important andgrowing research area. To realize a high-compression codec (coder and decoder), several image coding techniques have been proposed. Among these, motion compensated image coding is widely used to reduce the temporal redundancy, and the key to success of such scheme is to develop a good motion estimation technique to predict the current frame based on the previous ones. In the beginning of the thesis, a hybrid motion compensated coder is described to illustrate the importance of proposed algorithm and architecture. With regard to the computational complexity and implementation of VLSI architecture, the block matching algorithm is a good candidate for motion estimation. In this thesis, a fast hierarchical block matching algorithm and its VLSI array architectures are proposed. Based on a novel data flow, these two parts are integrated into an efficient system. The novelty of this new system is threefold. Firstly, it has high throughput.Secondly, it has good prediction quality. Thirdly, its hardware can be implemented without the limitations of the conventional hierarchical algorithms. The performance is evaluated from the viewpoint of current CMOStechnology. It shows that the real time processing of videophone and TV signals can be achieved for a single chip realization. The simulation results indicate that the prediction quality is close to the full search algorithm and zero-waiting cycle algorithm.
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Ansari, Rifqi, and Rifqi Ansari. "Developing a Hybrid Particle Swarm Optimization – Tabu Search for a Hierarchical Facility Location Problem." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/6752vv.
Full textAbstract:
碩士國立臺灣科技大學
工業管理系
102
Hierarchical facility location problem (HFLP) is an extended version of facility layout problem which aims to determine the location of facilities in a way that facilities in higher level can serve lower level efficiently. Particle swarm optimization (PSO) algorithms have been applied to a number of classical and real-world problems. However, since PSO is a stochastic search algorithm, it is likely to be failed to reach global value at the end of a run when the problem is too complicated. This study proposes a combination of PSO and TS for solving the hierarchical facility location problem (HFLP) called HPSO-TS. Moreover, this study also proposes the exact method branch and bound, genetic algorithm, and classical PSO to be compared to the proposed algorithm. To conform to the real world, this study considers the flow capacity in the networks or in other term the vehicle capacity, and in the results the optimal number of vehicle assignments also need to be considered. In this study, a mixed integer programming model for HFLP with flow capacity constraint is developed. The decisions to be made are locating a number of facilities on a set of potential sites, determining the network assignments, and number of flow assignments on the networks. The objective is to minimize the overall demand weighted distance travel, opening facilities cost, and flow assignments cost. A random key-based solution representation and decoding method is proposed for implementing HPSO-TS. The decoding method starts by transforming the particles into a priority list and then constructed as the assignment networks. Numerical results show that the proposed algorithm is effective and gives optimal or close to optimal solutions as compared with exact solutions in solving this kind of problems. Finally, the proposed algorithm is used to solve the study case of XYZ Company.
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Hsiao, Jen-Hui, and 蕭仁惠. "Using Hierarchical SVM Algorithm to Construct a Vocabulary Tree for Mobile Visual Search Applications." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/39578063997651257505.
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Weng, Chuan-Chi, and 翁傳奇. "Hierarchical Resource Classification Overlay Network (HRCON) with Efficient Search in DHT-based Structure P2P Networks." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/02358941570327551044.
Full textAbstract:
碩士朝陽科技大學
資訊工程系碩士班
94
The most significant challenge in designing a P2P file sharing system is providing a keyword search mechanism that allows users to efficiently locate desired files with short duration. DHT-based systems are highly scalable for locating data items with unique item identifier; however, DHTs do not support keyword search. While unstructured P2P systems like Gnutella are flexible enough to support keyword search, however, this system achieve poor scalability due to query flooding. As described above, structured and unstructured P2P networks are lack with the ability to achieve both scalability and keyword search capability simultaneously. In this paper, we proposed a Hierarchical Resource Classification Overlay Networks (HRCON) on top of DHT where each overlay is responsible for particular category of files. In our scheme, when a peer need a file that type related to belonging group, desired files could be obtained from the peers inside the group, which are topologically close. Clearly, content caching inside groups can further increase the efficiency of peer to peer communications by reduce the number of messages that need to get out of the group. Since there are often a large number of possibilities in keyword search, HRCON can greatly increase the performance by narrowed down the searching area.
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Chang, Chun-Wei, and 張鈞偉. "Using Shortest Search Time to Plan Optimal Traffic Paths Based on Hierarchical Servers and Wireless Sensor Networks." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/68124413487900602562.
Full textAbstract:
碩士朝陽科技大學
資訊管理系碩士班
96
To avoid a traffic jam on the road with a heavy load, it is important to collect the information for a Car-Agent (CAG) to approach the destination. Specially, Real-Time information is significant to help CAG to achieve the purpose mentioned above. Using a hierarchical server structure located at different location and processing the received data from the wireless sensors on the road, this thesis proposes a scheme to describe a shortest path for the CAGs. Besides the short geometric path needed for the CAGs, the shortest time is also needed to describe an optimal path for traveling. Comparing with the Accumulation History, the proposed scheme is with a benefit for a real time processing. Also, comparing with the previous method by Dijkstra, the proposed scheme employing the hierarchical server structure provides a time efficient method in the search of an optimal path.
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Doroodgar, Barzin. "A Learning-based Semi-autonomous Control Architecture for Robotic Exploration in Search and Rescue Environments." Thesis, 2011. http://hdl.handle.net/1807/30576.
Full textAbstract:
Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing cooperation and task sharing between a human operator and a robot with respect to tasks such as navigation, exploration and victim identification. Herein, a unique hierarchical reinforcement learning (HRL) -based semi-autonomous control architecture is presented for rescue robots operating in unknown and cluttered urban search and rescue (USAR) environments. The aim of the controller is to allow a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A new direction-based exploration technique and a rubble pile categorization technique are integrated into the control architecture for exploration of unknown rubble filled environments. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed control architecture.
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Adewumi, Aderemi Oluyinka. "Some improved genetic-algorithms based heuristics for global optimization with innovative applications." Thesis, 2010. http://hdl.handle.net/10539/8621.
Full textAbstract:
The research is a study of the efficiency and robustness of genetic algorithm to instances of both
discrete and continuous global optimization problems. We developed genetic algorithm based
heuristics to find the global minimum to problem instances considered.
In the discrete category, we considered two instances of real-world space allocation problems
that arose from an academic environment in a developing country. These are the university
timetabling problem and hostel space allocation problem. University timetabling represents a
difficult optimization problem and finding a high quality solution is a challenging task. Many
approaches, based on instances from developed countries, have been reported in the literature.
However, most developing countries are yet to appreciate the deployment of heuristics and
metaheuristics in handling the timetabling problem. We therefore worked on an instance from a
university in Nigeria to show the feasibility and efficiency of heuristic method to the timetabling
problem. We adopt a simplified bottom up approach in which timetable are build around
departments. Thus a small portion of real data was used for experimental testing purposes. As
with similar baseline studies in literature, we employ genetic algorithm to solve this instance and
show that efficient solutions that meet stated constraints can be obtained with the metaheuristics.
This thesis further focuses on an instance of university space allocation problem, namely the
hostel space allocation problem. This is a new instance of the space allocation problems that has
not been studied by metaheuristic researchers to the best of our knowledge. The problem aims at
the allocation of categories of students into available hostel space. This must be done without
violating any hard constraints but satisfying as many soft constraints as possible and ensuring
optimum space utilization. We identified some issues in the problem that helped to adapt
metaheuristic approach to solve it. The problem is multi-stage and highly constrained. We first
highlight an initial investigation based on genetic algorithm adapted to find a good solution
within the search space of the hostel space allocation problem. Some ideas are introduced to
increase the overall performance of initial results based on instance of the problem from our case
study. Computational results obtained are reported to demonstrate the effectiveness of the
solution approaches employed.
Sensitivity analysis was conducted on the genetic algorithm for the two SAPs considered to
determine the best parameter values that consistently give good solutions. We noted that the
genetic algorithms perform well specially, when repair strategies are incorporated. This thesis
pioneers the application of metaheuristics to solve the hostel space allocation problem. It
provides a baseline study of the problem based on genetic algorithms with associated test data
sets. We report the best known results for the test instances.
It is a known fact that many real-life problems are formulated as global optimization problems
with continuous variables. On the continuous global optimization category therefore, we focus
on improving the efficiency and reliability of real coded genetic algorithm for solving
unconstrained global optimization, mainly through hybridization with exploratory features.
Hybridization has widely been recognized as one of the most attractive approach to solving
unconstrained global optimization. Literatures have shown that hybridization helps component
heuristics to taking advantage of their individual strengths while avoiding their weaknesses. We
therefore derived three modified forms of real coded genetic algorithm by hybridizing the
standard real-coded genetic algorithm with pattern search and vector projection. These are
combined to form three new algorithms namely, RCGA-PS, RCGA-P, and RCGA-PS-P. The
hybridization strategy used and results obtained are reported and compared with the standard
real-coded genetic algorithm. Experimental studies show that all the modified algorithms
perform better than the original algorithm.
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Huang, Wei-Yin, and 黃威穎. "Hierarchically Dynamic Clustering of Web Search Results." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/16206064099000268747.
Full textAbstract:
碩士元智大學
資訊管理學系
94
This study proposes a hierarchical clustering method for dynamic clustering of web search results. The resulting tree of clusters can help users efficiently locate the relevant web pages they are interested in. The proposed method extracts feature tokens from the page titles and snippets of search results, and based on an indicator calculated by the coverage and distinctiveness of these feature tokens, determines the clustering concepts, the cluster labels and the number of clusters. Additionally, the proposed method allows a web page to be grouped into several clusters, also it pushes the high ranking web pages into the leading clusters. This study determined the clustering termination condition based on preliminary evaluation results of reach time for several Chinese and English hot keywords. A user study showed that the users are more satisfied with the proposed system than with the commercial system, Vivisimo, and are slightly satisfied with the proposed system than with the related method, DisCover, using English and Chinese hot keywords. Moreover, a performance measure on reach time confirmed that the proposed system out-performs Vivisimo, and performs slightly better than DisCover.