Gotowe bibliografie tematyczne / Query algorithm

Gotowa bibliografia na temat „Query algorithm”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 20 lutego 2023

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Artykuły w czasopismach na temat "Query algorithm"

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Joshi, Mukul, i Praveen Ranjan Srivastava. "Query Optimization". International Journal of Intelligent Information Technologies 9, nr 1 (styczeń 2013): 40–55. http://dx.doi.org/10.4018/jiit.2013010103.

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Query optimization is an important aspect in designing database management systems, aimed to find an optimal query execution plan so that overall time of query execution is minimized. Multi join query ordering (MJQO) is an integral part of query optimizer. This paper aims to propose a solution for MJQO problem, which is an NP complete problem. This paper proposes a heuristic based algorithm as a solution of MJQO problem. The proposed algorithm is a combination of two basic search algorithms, cuckoo and tabu search. Simulation shows some exciting results in favour of the proposed algorithm and concludes that proposed algorithm can solve MJQO problem in less amount of time than the existing methods.
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Li, Feng, i Hai Ying Wang. "Study on Distributed Database Query Optimization". Applied Mechanics and Materials 536-537 (kwiecień 2014): 540–44. http://dx.doi.org/10.4028/www.scientific.net/amm.536-537.540.

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This paper presents a heterogeneous sensor networks to improve query processing mechanism. Analysis of the advantages and disadvantages of centralized query processing algorithm is proposed based on the spatial distance distributed query processing algorithm based on semantic similarity and distributed query processing algorithms for query execution processes described. Use simulation to choose better coverage and semantic similarity by half, and centralized query processing algorithm, based on the spatial distance distributed algorithms, distributed algorithms and performance-based semantic distributed hybrid algorithm were compared.
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Xu, Jialu, i Feiyue Ye. "Query Recommendation Using Hybrid Query Relevance". Future Internet 10, nr 11 (19.11.2018): 112. http://dx.doi.org/10.3390/fi10110112.

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With the explosion of web information, search engines have become main tools in information retrieval. However, most queries submitted in web search are ambiguous and multifaceted. Understanding the queries and mining query intention is critical for search engines. In this paper, we present a novel query recommendation algorithm by combining query information and URL information which can get wide and accurate query relevance. The calculation of query relevance is based on query information by query co-concurrence and query embedding vector. Adding the ranking to query-URL pairs can calculate the strength between query and URL more precisely. Empirical experiments are performed based on AOL log. The results demonstrate the effectiveness of our proposed query recommendation algorithm, which achieves superior performance compared to other algorithms.
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Meng, Yao. "Study on Query Optimization of Distributed Database". Applied Mechanics and Materials 533 (luty 2014): 448–51. http://dx.doi.org/10.4028/www.scientific.net/amm.533.448.

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Distributed query optimization in contemporary distributed database system increasingly important role, excellent query optimizer algorithm can effectively improve the query performance of the system. This article will be distributed query optimization hybrid algorithm is applied to improve the performance of distributed query optimization algorithms. Through simulation experiments and comparing two improved algorithms and the merits of the original algorithm, results were analyzed and show that the improved algorithm is better than the original algorithm has been improved to some extent in achieving cost efficiency and other aspects.
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Yang, Ze Xue, i Zhong Xiao Hao. "Spatial Join Queries Based on QR-Tree". Advanced Materials Research 187 (luty 2011): 752–57. http://dx.doi.org/10.4028/www.scientific.net/amr.187.752.

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Spatial join query is a most important query in the spatial database.How to improve the efficiency of a spatial join is a serious question.In this paper,we propose a new algorithm to process spatial join problem.The algorithm is based on the QR-tree,which combines the good property of the R-tree and quadtree.By dividing the space into several subspaces,the algorithm implement the spatial join query on the small R-tree.We compare the algorithm with the R-tree join algorithm of Brinkhoff. Experiments demonstrate the proposed algorithms have high query efficiency.
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Li, Xin, Huayan Yu, Ligang Yuan i Xiaolin Qin. "Query Optimization for Distributed Spatio-Temporal Sensing Data Processing". Sensors 22, nr 5 (23.02.2022): 1748. http://dx.doi.org/10.3390/s22051748.

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The unprecedented development of Internet of Things (IoT) technology produces humongous amounts of spatio-temporal sensing data with various geometry types. However, processing such datasets is often challenging due to high-dimensional sensor data geometry characteristics, complex anomalistic spatial regions, unique query patterns, and so on. Timely and efficient spatio-temporal querying significantly improves the accuracy and intelligence of processing sensing data. Most existing query algorithms show their lack of supporting spatio-temporal queries and irregular spatial areas. In this paper, we propose two spatio-temporal query optimization algorithms based on SpatialHadoop to improve the efficiency of query spatio-temporal sensing data: (1) spatio-temporal polygon range query (STPRQ), which aims to find all records from a polygonal location in a time interval; (2) spatio-temporal k nearest neighbors query (STkNNQ), which directly searches the query point’s k closest neighbors. To optimize the STkNNQ algorithm, we further propose an adaptive iterative range optimization algorithm (AIRO), which can optimize the iterative range of the algorithm according to the query time range and avoid querying irrelevant data partitions. Finally, extensive experiments based on trajectory datasets demonstrate that our proposed query algorithms can significantly improve query performance over baseline algorithms and shorten response time by 81% and 35.6%, respectively.
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XIE, Kun, Ji-Gang WEN, Da-Fang ZHANG i Gao-Gang XIE. "Bloom Filter Query Algorithm". Journal of Software 20, nr 1 (7.04.2009): 96–108. http://dx.doi.org/10.3724/sp.j.1001.2009.00096.

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Bai, Luyi, Jinyao Wang, Chengyu Zhang i Xiangfu Meng. "Query Relaxation and Result Ranking for Uncertain Spatiotemporal XML Data". Journal of Database Management 33, nr 1 (1.01.2022): 1–19. http://dx.doi.org/10.4018/jdm.313970.

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Due to the widespread uses of uncertain spatiotemporal data, web ordinary users have access to query these data in various ways. However, users often cannot accurately give query constraints so that the query results may be empty or very few. Traditional algorithms cannot be used to deal with uncertain spatiotemporal data because they have no relaxation query on spatiotemporal attributes. Therefore, in this paper, the authors propose new flexible query algorithms, which add relaxation query processing for spatiotemporal attributes. Considering that XML has great advantages in exchanging and representing spatiotemporal data, they propose an uncertain spatiotemporal data model based on XML. According to the different number of relaxing attributes, they give SingleRelaxation algorithm and MultipleRelaxation algorithm. In addition, a T-List structure is designed to quickly locate the nodes' positions of uncertain spatiotemporal data, and RSort algorithm is proposed to sort accurate query results and extended query results. The experimental results show the superiority of the approach.
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Kim, Hyeong-Jin, Hyunjo Lee, Yong-Ki Kim i Jae-Woo Chang. "Privacy-preserving kNN query processing algorithms via secure two-party computation over encrypted database in cloud computing". Journal of Supercomputing 78, nr 7 (17.01.2022): 9245–84. http://dx.doi.org/10.1007/s11227-021-04286-2.

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AbstractSince studies on privacy-preserving database outsourcing have been spotlighted in a cloud computing, databases need to be encrypted before being outsourced to the cloud. Therefore, a couple of privacy-preserving kNN query processing algorithms have been proposed over the encrypted database. However, the existing algorithms are either insecure or inefficient. Therefore, in this paper we propose a privacy-preserving kNN query processing algorithm via secure two-party computation on the encrypted database. Our algorithm preserves both data privacy and query privacy while hiding data access patterns. For this, we propose efficient and secure protocols based on Yao’s garbled circuit. To achieve a high degree of efficiency in query processing, we also propose a parallel kNN query processing algorithm using encrypted random value pool. Through our performance analysis, we verify that our proposed algorithms outperform the existing ones in terms of a query processing cost.
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Xu, Hong Bo, i Nian Min Yao. "A Range Query Parallel Algorithm in High-Dimensional Space". Applied Mechanics and Materials 263-266 (grudzień 2012): 2308–13. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2308.

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The performance of the spatial range query algorithms based on Brute-Force method, R-tree, VA-file and NB-tree suffers greatly in high-dimensional space. So the reduction of the dimensionality is the key to the spatial range query in high-dimensional space. The paper uses the parallel technique to present a spatial range query parallel algorithm in high-dimensional space. The algorithm transforms d-dimensional spatial range query to the linear space on d slave node processors. The d slave node processors run parallel. The master node processor only need calculate the union of d results which d slave node processors return. The experimental results indicate that its performance is better than that of the spatial range query algorithms based on Brute-Force method, R-tree, VA-file, NB-tree.
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Rozprawy doktorskie na temat "Query algorithm"

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Cheng, Jiang. "Preserving query privacy with a query-based memorizing algorithm". Thesis, Wichita State University, 2014. http://hdl.handle.net/10057/10950.

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Query privacy is a critical concern to users of location-based services. A majority of existing query privacy protection techniques are based on the notion of k-anonymity, wherein a user's exact location is obfuscated into a spatial range containing at least k users, called the cloaking region. Thus, the user who issues the query cannot be distinguished from k-1 other users. However, when mobile users issue continuous queries using such a k-anonymity scheme, an adversary can exploit the overlapped areas of the corresponding cloaking regions to determine the query issuer with a significantly higher probability. This thesis proposes a query-based memorizing algorithm to specifically address this issue. The main idea in this thesis is to memorize the identity of the users in an anonymity set or cloaking region. When a user issues sequential location-based queries, the cloaking regions are determined such that they include a maximum number of users that have appeared in the past cloaking regions. The query-based memorizing approach is empirically evaluated by means of simulation experiments and a detailed comparative analysis with three other popular privacy protection algorithms using standard privacy metrics is performed. The results show that the proposed algorithm efficiently protects users' query privacy against the overlapped area attack, especially when users are highly mobile.
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
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Suryavanshi, Chetna. "Query AutoAwesome". DigitalCommons@USU, 2019. https://digitalcommons.usu.edu/etd/7546.

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This research investigates how to improve legacy queries. Legacy queries are queries that programmers have coded and are used in applications. A database application typically has tens to hundreds of such queries. One way to improve legacy queries is to add new, interesting queries that are similar to or based on the set of queries. We propose Query AutoAwesome, a tool to generate new queries from legacy queries. The Query AutoAwesome philosophy is taken from Google’s AutoAwesomizer tool for photos, which automatically improves a photo uploaded to Google by animating the photo or adding special effects. In a similar vein, Query AutoAwesome automatically enhances a query by ingesting a database and the query. Query AutoAwesome produces a set of enhanced queries that a user can then choose to use or discard. A key problem that we solve is that the space of potential enhancements is large, so we introduce objective functions to narrow the search space to a tractable space. We describe our plans for implementing Query AutoAwesome and discuss our ideas for future work.
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Lin, Han-Hsuan. "Topics in quantum algorithms : adiabatic algorithm, quantum money, and bomb query complexity". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/99300.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Physics, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 111-115).
In this thesis, I present three results on quantum algorithms and their complexity. The first one is a numerical study on the quantum adiabatic algorithm( QAA) . We tested the performance of the QAA on random instances of MAX 2-SAT on 20 qubits and showed 3 strategics that improved QAA's performance, including a counter intuitive strategy of decreasing the overall evolution time. The second result is a security proof for the quantum money by knots proposed by Farhi et. al. We proved that quantum money by knots can not be cloned in a black box way unless graph isomorphism is efficiently solvable by a quantum computer. Lastly we defined a modified quantum query model, which we called bomb query complexity B(J), inspired by the Elitzur-Vaidman bomb-testing problem. We completely characterized bomb query complexity be showing that B(f) = [Theta](Q(f)2 ). This result implies a new method to find upper bounds on quantum query complexity, which we applied on the maximum bipartite matching problem to get an algorithm with O(n1.75) quantum query complexity, improving from the best known trivial O(n2 ) upper bound.
by Han-Hsuan Lin.
Ph. D.
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Samara, Rafat. "TOP-K AND SKYLINE QUERY PROCESSING OVER RELATIONAL DATABASE". Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Informationsteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-20108.

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Top-k and Skyline queries are a long study topic in database and information retrieval communities and they are two popular operations for preference retrieval. Top-k query returns a subset of the most relevant answers instead of all answers. Efficient top-k processing retrieves the k objects that have the highest overall score. In this paper, some algorithms that are used as a technique for efficient top-k processing for different scenarios have been represented. A framework based on existing algorithms with considering based cost optimization that works for these scenarios has been presented. This framework will be used when the user can determine the user ranking function. A real life scenario has been applied on this framework step by step. Skyline query returns a set of points that are not dominated (a record x dominates another record y if x is as good as y in all attributes and strictly better in at least one attribute) by other points in the given datasets. In this paper, some algorithms that are used for evaluating the skyline query have been introduced. One of the problems in the skyline query which is called curse of dimensionality has been presented. A new strategy that based on the skyline existing algorithms, skyline frequency and the binary tree strategy which gives a good solution for this problem has been presented. This new strategy will be used when the user cannot determine the user ranking function. A real life scenario is presented which apply this strategy step by step. Finally, the advantages of the top-k query have been applied on the skyline query in order to have a quickly and efficient retrieving results.
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Pielech, Bradford Charles. "Adaptive Scheduling Algorithm Selection in a Streaming Query System". Digital WPI, 2004. https://digitalcommons.wpi.edu/etd-theses/79.

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Many modern applications process queries over unbounded streams of data. These applications include tracking financial data from international markets, intrusion detection in networks, monitoring remote sensors, and monitoring patients vital signs. These data streams arrive in real time, are unbounded in length and have unpredictable arrival patterns due to external uncontrollable factors such as network congestion or weather in the case of remote sensors. This thesis presents a novel technique for adapting the execution of stream queries that, to my knowledge, is not present in any other continuous query system to date. This thesis hypothesizes that utilizing a single scheduling algorithm to execute a continuous query, as is employed in other state-of-the-art continuous query systems, is not sufficient because existing scheduling algorithms all have inherent flaws or tradeoffs. Thus, one scheduling algorithm cannot optimally meet an arbitrary set of Quality of Service (QoS) requirements. Therefore, to meet unique features of specific monitoring applications, an adaptive strategy selector guidable by QoS requirements was developed. The adaptive strategy selector monitors the effects of its behavior on its environment through a feedback mechanism, with the aim of exploiting previously beneficial behavior and exploring alternative behavior. The feedback mechanism is guided by qualitatively comparing how well each algorithm has met the QoS requirements. Then the next scheduling algorithm is chosen by spinning a roulette wheel where each candidate is chosen with a probability equal to its performance score. The adaptive algorithm is general, being able to employ any candidate scheduling algorithm and to react to any combination of quality of service preferences. As part of this thesis, the Raindrop system was developed as exploratory test bed in which to conduct an experimental study. In that experimental study, the adaptive algorithm was shown to be effective in outperforming single scheduling algorithms for many QoS combinations and data arrival patterns.
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Staicu, Laurian. "Multiple query points parallel search algorithm (Comb algorithm) for multimedia database systems". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ59340.pdf.

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Lim, Heechul. "Evaluation of Shortest Path Query Algorithm in Spatial Databases". Thesis, University of Waterloo, 2003. http://hdl.handle.net/10012/1085.

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Many variations of algorithms for finding the shortest path in a large graph have been introduced recently due to the needs of applications like the Geographic Information System (GIS) or Intelligent Transportation System (ITS). The primary subjects of those algorithms are materialization and hierarchical path views. Some studies focus on the materialization and sacrifice the pre-computational costs and storage costs for faster computation of a query. Other studies focus on the shortest-path algorithm, which has less pre-computation and storage but takes more time to compute the shortest path. The main objective of this thesis is to accelerate the computation time for the shortest-path queries while keeping the degree of materialization as low as possible. This thesis explores two different categories: 1) the reduction of the I/O-costs for multiple queries, and 2) the reduction of search spaces in a graph. The thesis proposes two simple algorithms to reduce the I/O-costs, especially for multiple queries. To tackle the problem of reducing search spaces, we give two different levels of materializations, namely, the boundary set distance matrix and x-Hop sketch graph, both of which materialize the shortest-path view of the boundary nodes in a partitioned graph. Our experiments show that a combination of the suggested solutions for 1) and 2) performs better than the original Disk-based SP algorithm [7], on which our work is based, and requires much less storage than HEPV [3].
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Pielech, Bradford Charles. "Adaptive scheduling algorithm selection in a streaming query system". Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0113104-194126.

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Carraher, Lee A. "A Parallel Algorithm for Query Adaptive, Locality Sensitive Hash Search". University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337886738.

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Chen, Chen. "An evaluation of a 2-way semijoin distributed query processing algorithm". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ62199.pdf.

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Książki na temat "Query algorithm"

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Koukoudakis, Alexandros. Visualisation decision algorithm for temporal database management system. Manchester: UMIST, 1996.

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Ma, Zhe. Dynamic query algorithms for human-computer interaction based on information gain and the multi-layer perceptron. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1996.

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Use of genetic algorithms for query improvement in information retrieval based on a vector space model. Ann Arbor, Mich: University Microfilms International, 1994.

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S, Liu Jane W., i United States. National Aeronautics and Space Administration., red. Monotonically improving approximate answers to relational algebra queries. [Washington, DC: National Aeronautics and Space Administration, 1989.

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Boudreau, Joseph F., i Eric S. Swanson. Templates, the standard C++ library, and modern C++. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198708636.003.0017.

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This chapter is devoted to programming techniques which rely on the C++ template mechanism. This mechanism, which is the basis of a computing style known as generic programming, allows whole families of functions and classes to be easily written. It is described early in the chapter. A host of extremely useful template functions and classes is universally available in the C++ standard library, including container classes (vector, list, set, and map) and algorithms used to sort, shuffle, and otherwise manipulate or query their contents. The chapter closes with an introduction to the newer constructs of modern C++: smart pointers, lambda functions, the auto keyword, range-based for loops, and more. An application to group theory is explored in the exercises.
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Tzoukermann, Evelyne, Judith L. Klavans i Tomek Strzalkowski. Information Retrieval. Redaktor Ruslan Mitkov. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780199276349.013.0029.

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Information retrieval (IR) involves retrieving information from stored data, through user queries or pre-formulated user profiles. The information can be in any format. IR typically advances over four broad stages viz., identification of text types, document preprocessing, document indexing, and query processing and matching the same to documents. Although NLP has a role to play in IR, the procedural complexities of the latter impede determination of the stage of incorporation of the former into the latter. Earliest attempts at connecting NLP with IR, were extremely ambitious, proposing concepts instead of terms, as complex structures, to be compared using sophisticated algorithms. In its current state, IR still comes in handy, to retrieve information from various thesauri and ontologies, both in general-purpose lexical databases, as well as those categorizing knowledge in particular scientific and trade domains. However, NLP has yet to prove a better compatibility with IR, in enhancing the latter.
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Części książek na temat "Query algorithm"

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Dombrovskaya, Henrietta, Boris Novikov i Anna Bailliekova. "Ultimate Optimization Algorithm". W PostgreSQL Query Optimization, 303–8. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6885-8_15.

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Shekhar, Shashi, i Hui Xiong. "Range Query Algorithm". W Encyclopedia of GIS, 949. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1076.

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Shahri, Saied Haidarian, i Hasan Jamil. "An Extendable Meta-learning Algorithm for Ontology Mapping". W Flexible Query Answering Systems, 418–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04957-6_36.

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Benadjmi, Noussaiba, i Khaled Walid Hidouci. "New Variants of Hash-Division Algorithm for Tolerant and Stratified Division". W Flexible Query Answering Systems, 99–111. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59692-1_9.

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Alfano, Gianvincenzo. "An Efficient Algorithm for Computing the Set of Semi-stable Extensions". W Flexible Query Answering Systems, 139–51. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27629-4_15.

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Shin, Hyoseop, i Minsoo Lee. "An Efficient Branch Query Rewriting Algorithm for XML Query Optimization". W Lecture Notes in Computer Science, 1629–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11575801_45.

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Vijay Kumar, T. V., i Shina Panicker. "Generating Query Plans for Distributed Query Processing Using Genetic Algorithm". W Information Computing and Applications, 765–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25255-6_97.

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Dias, Steffy, Shweta Kolhe, Ruchi Shinde, Richa Chaudhari i Revati M. Wahul. "Query Time Optimization Using Hungarian Algorithm". W Lecture Notes in Electrical Engineering, 271–76. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8715-9_32.

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Singh, Vikram, Siddhant Garg i Pradeep Kaur. "Efficient Algorithm for Web Search Query Reformulation Using Genetic Algorithm". W Advances in Intelligent Systems and Computing, 459–70. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2734-2_46.

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Wang, Ziqiang, i Boqin Feng. "Optimal Genetic Query Algorithm for Information Retrieval". W Parallel and Distributed Processing and Applications, 888–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30566-8_102.

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Streszczenia konferencji na temat "Query algorithm"

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Wang, Manzi, Haidong Fu i Fangfang Xu. "RDF Multi-query Optimization Algorithm for Query Rewriting Using Common Subgraphs". W the 3rd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3331453.3361278.

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Zhang, Bin, i Feiyue Ye. "Semantics Based Multi-XML Query Algorithm". W 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.385.

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Guttoski, Pryscila Barvik, Marcos Sfair Sunye i Fabiano Silva. "Kruskal's Algorithm for Query Tree Optimization". W 11th International Database Engineering and Applications Symposium (IDEAS 2007). IEEE, 2007. http://dx.doi.org/10.1109/ideas.2007.4318118.

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Zeboudj, Meriem, i Khaled Belkadi. "Web Query Reformulation Using FireFly Algorithm". W 2020 Second International Conference on Embedded & Distributed Systems (EDiS). IEEE, 2020. http://dx.doi.org/10.1109/edis49545.2020.9296463.

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Goyal, A., A. Thakral i G. K. Sharma. "Improved A* Algorithm For Query Optimization". W 20th Conference on Modelling and Simulation. ECMS, 2006. http://dx.doi.org/10.7148/2006-0472.

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Alviano, Mario. "Query Answering in Propositional Circumscription". W Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/231.

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Propositional circumscription defines a preference relation over the models of a propositional theory, so that models being subset-minimal on the interpretation of a set of objective atoms are preferred.The complexity of several computational tasks increase by one level in the polynomial hierarchy due to such a preference relation;among them there is query answering, which amounts to decide whether there is an optimal model satisfying the query.A complete algorithm for query answering is obtained by searching for a model, not necessarily an optimal one, that satisfies the query, and such that no model unsatisfying the query is more preferred.If the query or its complement are among the objective atoms, the algorithm has a simpler behavior, which is also described in the paper.Moreover, an incomplete algorithm is obtained by searching for a model satisfying both the query and an objective atom being unit-implied by the theory extended with the complement of the query.A prototypical implementation is tested on instances from the 2nd International Competition on Computational Models of Argumentation (ICCMA'17).
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Tamine, L., i M. Boughanem. "Query optimisation using an improved genetic algorithm". W the ninth international conference. New York, New York, USA: ACM Press, 2000. http://dx.doi.org/10.1145/354756.354842.

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Robertson, Glen, i Xiaoying Gao. "Improving AbraQ: An Automatic Query Expansion Algorithm". W 2010 IEEE/ACM International Conference on Web Intelligence-Intelligent Agent Technology (WI-IAT). IEEE, 2010. http://dx.doi.org/10.1109/wi-iat.2010.95.

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Al-Khateeb, Belal, Ali J. Al-Kubaisi i Sufyan T. Al-Janabi. "Query reformulation using WordNet and genetic algorithm". W 2017 Annual Conference on New Trends in Information & Communications Technology Applications (NTICT). IEEE, 2017. http://dx.doi.org/10.1109/ntict.2017.7976138.

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HARB, H., i L. CHEN. "A QUERY BY EXAMPLE MUSIC RETRIEVAL ALGORITHM". W Proceedings of the 4th European Workshop on Image Analysis for Multimedia Interactive Services. WORLD SCIENTIFIC, 2003. http://dx.doi.org/10.1142/9789812704337_0023.

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Raporty organizacyjne na temat "Query algorithm"

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Thost, Veronika, Jan Holste i Özgür Özçep. On Implementing Temporal Query Answering in DL-Lite. Technische Universität Dresden, 2015. http://dx.doi.org/10.25368/2022.218.

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Ontology-based data access augments classical query answering over fact bases by adopting the open-world assumption and by including domain knowledge provided by an ontology. We implemented temporal query answering w.r.t. ontologies formulated in the Description Logic DL-Lite. Focusing on temporal conjunctive queries (TCQs), which combine conjunctive queries via the operators of propositional linear temporal logic, we regard three approaches for answering them: an iterative algorithm that considers all data available; a window-based algorithm; and a rewriting approach, which translates the TCQs to be answered into SQL queries. Since the relevant ontological knowledge is already encoded into the latter queries, they can be answered by a standard database system. Our evaluation especially shows that implementations of both the iterative and the window-based algorithm answer TCQs within a few milliseconds, and that the former achieves a constant performance, even if data is growing over time.
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Rigotti, Christophe, i Mohand-Saïd Hacid. Representing and Reasoning on Conceptual Queries Over Image Databases. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.89.

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The problem of content management of multimedia data types (e.g., image, video, graphics) is becoming increasingly important with the development of advanced multimedia applications. Traditional database management systems are inadequate for the handling of such data types. They require new techniques for query formulation, retrieval, evaluation, and navigation. In this paper we develop a knowledge-based framework for modeling and retrieving image data by content. To represent the various aspects of an image object's characteristics, we propose a model which consists of three layers: (1) Feature and Content Layer, intended to contain image visual features such as contours, shapes,etc.; (2) Object Layer, which provides the (conceptual) content dimension of images; and (3) Schema Layer, which contains the structured abstractions of images, i.e., a general schema about the classes of objects represented in the object layer. We propose two abstract languages on the basis of description logics: one for describing knowledge of the object and schema layers, and the other, more expressive, for making queries. Queries can refer to the form dimension (i.e., information of the Feature and Content Layer) or to the content dimension (i.e., information of the Object Layer). These languages employ a variable free notation, and they are well suited for the design, verification and complexity analysis of algorithms. As the amount of information contained in the previous layers may be huge and operations performed at the Feature and Content Layer are time-consuming, resorting to the use of materialized views to process and optimize queries may be extremely useful. For that, we propose a formal framework for testing containment of a query in a view expressed in our query language. The algorithm we propose is sound and complete and relatively efficient.
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Rigotti, Christophe, i Mohand-Saïd Hacid. Representing and Reasoning on Conceptual Queries Over Image Databases. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.89.

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The problem of content management of multimedia data types (e.g., image, video, graphics) is becoming increasingly important with the development of advanced multimedia applications. Traditional database management systems are inadequate for the handling of such data types. They require new techniques for query formulation, retrieval, evaluation, and navigation. In this paper we develop a knowledge-based framework for modeling and retrieving image data by content. To represent the various aspects of an image object's characteristics, we propose a model which consists of three layers: (1) Feature and Content Layer, intended to contain image visual features such as contours, shapes,etc.; (2) Object Layer, which provides the (conceptual) content dimension of images; and (3) Schema Layer, which contains the structured abstractions of images, i.e., a general schema about the classes of objects represented in the object layer. We propose two abstract languages on the basis of description logics: one for describing knowledge of the object and schema layers, and the other, more expressive, for making queries. Queries can refer to the form dimension (i.e., information of the Feature and Content Layer) or to the content dimension (i.e., information of the Object Layer). These languages employ a variable free notation, and they are well suited for the design, verification and complexity analysis of algorithms. As the amount of information contained in the previous layers may be huge and operations performed at the Feature and Content Layer are time-consuming, resorting to the use of materialized views to process and optimize queries may be extremely useful. For that, we propose a formal framework for testing containment of a query in a view expressed in our query language. The algorithm we propose is sound and complete and relatively efficient.
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Ecke, Andreas, i Anni-Yasmin Turhan. Similarity Measures for Computing Relaxed Instances w.r.t. General EL-TBoxes. Technische Universität Dresden, 2013. http://dx.doi.org/10.25368/2022.202.

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The notion of concept similarity is central to several ontology tasks and can be employed to realize relaxed versions of classical reasoning services. In this paper we investigate the reasoning service of answering instance queries in a relaxed fashion, where the query concept is relaxed by means of a concept similarity measure (CSM). To this end we investigate CSMs that assess the similarity of EL-concepts defined w.r.t. a general EL-TBox. We derive such a family of CSMs from a family of similarity measures for finite interpretations and show in both cases that the resulting measures enjoy a collection of formal properties. These properties allow us to devise an algorithm for computing relaxed instances w.r.t. general EL-TBoxes, where users can specify the „appropriate“ notion of similarity by instanciating our CSM appropriately.
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Gil, Oliver Fernández, i Anni-Yasmin Turhan. Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics. Technische Universität Dresden, 2020. http://dx.doi.org/10.25368/2022.261.

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Classical regular path queries (RPQs) can be too restrictive for some applications and answering such queries under approximate semantics to relax the query is desirable. While for answering regular path queries over graph databases under approximate semantics algorithms are available, such algorithms are scarce for the ontology-mediated setting. In this paper we extend an approach for answering RPQs over graph databases that uses weighted transducers to approximate paths from the query in two ways. The first extension is to answering approximate conjunctive 2-way regular path queries (C2RPQs) over graph databases and the second is to answering C2RPQs over ELH and DL-LiteR ontologies. We provide results on the computational complexity of the underlying reasoning problems and devise approximate query answering algorithms.
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