Dissertations / Theses: 'Views selection'

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Gupta, Shalu. "View Selection for Query-Evaluation Efficiency using Materialized Views." NCSU, 2005. http://www.lib.ncsu.edu/theses/available/etd-07142005-142452/.

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The purpose of this research is to show the use of derived data such as materialized views for run time optimization of aggregate queries. In this thesis, we show the trade off between the time taken to design the views Vs the query run time. We have designed a system called Query Performance Enhancement by Tuning (QPET) which implements the idea of designing and using materialized views to answer frequent aggregate queries.

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Indelli, Pisano Valentina. "Reducing the View Selection Problem through Code Modeling: Static and Dynamic approaches." Doctoral thesis, Universita degli studi di Salerno, 2017. http://hdl.handle.net/10556/2617.

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2015 - 2016
Data warehouse systems aim to support decision making by providing users with the appropriate information at the right time. This task is particularly challenging in business contexts where large amount of data is produced at a high speed. To this end, data warehouses have been equipped with Online Analytical Processing tools that help users to make fast and precise decisions througt the execution of complex queries. Since the computation of these queries is time consuming, data warehouses precompute a set of materialized views answering to the workload queries. This thesis work defines a process to determine the minimal set of workload queries and the set of views to materialize. The set of queries is represented by an optimized lattice structure used to select the views to be materialized according to the processing time costs and the view storage space. The minimal set of required Online Analytical Processing queries is computer by analyzing the data model defined with the visual language CoDe (Complexity Design). The latter allows to conceptually organizatio the visualization of data reports and to generate visualizations of data obtained from data-‐mart queries. CoDe adopts a hybrid modeling process combining two main methodologieser-‐driven and data- driven. The first aims to create a model according to the user knowledge, re-quirements, and analysis needs, whilst the latter has in charge to concretize data and their relationships in the model through Online Analytical Processing queries. Since the materialized views change over time, we also propose a dynamic process that allows users to upgrade the CoDe model with a context-‐aware editor, build an optimized lattice structure able to minimize the effort to recalculate it,and propose the new set of views to materialize Moreover, the process applies a Markov strategy to predict whether the views need to be recalculate or not according to the changes of the model. The effectiveness of the proposed techniques has been evaluated on a real world data warehouse. The results revealed that the Markov strategy gives a better set of solutions in term of storage space and total processing cost. [edited by author]
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Pistellato, Mara <1991&gt. "Robust Joint Selection of Camera Orientations and Feature Projections over Multiple Views." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/8799.

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A number of critical factors arises when a complex 3D scene is to be reconstructed by means of a large sequence of different views. Some of them are related to the ability to recover the correct identity and the accurate projection of each observed feature. Other sources of error are tied to the reliability of the orientation estimate for each view. Here we propose a method that tries to solve both problems at the same time, while being also inherently resilient to outliers. At the core of the approach stands a widely adopted game-theoretical selection technique, which has already been successfully adopted to address similar tasks. The original inception, however, has been further refined to allow both better accuracy and tighter selection, as well as a greatly reduced memory consumption and computation complexity. By exploiting these enhancements, we were able to apply our technique to real-wolrd scenarios involving several hundreds of view points and tens of thousands of independent observations.

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Helle, Valeria, Andra-Stefania Negus, and Jakob Nyberg. "Improving armed conflict prediction using machine learning : ViEWS+." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-354845.

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Our project, ViEWS+, expands the software functionality of the Violence EarlyWarning System (ViEWS). ViEWS aims to predict the probabilities of armed conflicts in the next 36 months using machine learning. Governments and policy-makers may use conflict predictions to decide where to deliver aid and resources, potentially saving lives. The predictions use conflict data gathered by ViEWS, which includes variables like past conflicts, child mortality and urban density. The large number of variables raises the need for a selection tool to remove those that are irrelevant for conflict prediction. Before our work, the stakeholders used their experience and some guesswork to pick the variables, and the predictive function with its parameters. Our goals were to improve the efficiency, in terms of speed, and correctness of the ViEWS predictions. Three steps were taken. Firstly, we made an automatic variable selection tool. This helps researchers use fewer, more relevant variables, to save time and resources. Secondly, we compared prediction functions, and identified the best for the purpose of predicting conflict. Lastly, we tested how parameter values affect the performance of the chosen functions, so as to produce good predictions but also reduce the execution time. The new tools improved both the execution time and the predictive correctness of the system compared to the results obtained prior to our project. It is now nine times faster than before, and its correctness has improved by a factor of three. We believe our work leads to more accurate conflict predictions, and as ViEWS has strong connections to the European Union, we hope that decision makers can benefit from it when trying to prevent conflicts.
I detta projekt, vilket vi valt att benämna ViEWS+, har vi förbättrat olika aspekter av ViEWS (Violence Early-Warning System), ett system som med maskinlärning försöker förutsäga var i världen väpnade konflikter kommer uppstå. Målet med ViEWS är att kunna förutsäga sannolikheten för konflikter så långt som 36 månader i framtiden. Målet med att förutsäga sannoliketen för konflikter är att politiker och beslutsfattare ska kunna använda dessa kunskaper för att förhindra dem. Indata till systemet är konfliktdata med ett stort antal egenskaper, så som tidigare konflikter, barnadödlighet och urbanisering. Dessa är av varierande användbarhet, vilket skapar ett behov för att sålla ut de som inte är användbara för att förutsäga framtida konflikter. Innan vårt projekt har forskarna som använder ViEWS valt ut egenskaper för hand, vilket blir allt svårare i och med att fler introduceras. Forskargruppen hade även ingen formell metodik för att välja parametervärden till de maskinlärningsfunktioner de använder. De valde parametrar baserat på erfarenhet och känsla, något som kan leda till onödigt långa exekveringstider och eventuellt sämre resultat beroende på funktionen som används. Våra mål med projektet var att förbättra systemets produktivitet, i termer av exekveringstid och säkerheten i förutsägelserna. För att uppnå detta utvecklade vi analysverktyg för att försöka lösa de existerande problemen. Vi har utvecklat ett verktyg för att välja ut färre, mer användbara, egenskaper från datasamlingen. Detta gör att egenskaper som inte tillför någon viktig information kan sorteras bort vilket sparar exekveringstid. Vi har även jämfört prestandan hos olika maskinlärningsfunktioner, för att identifiera de bäst lämpade för konfliktprediktion. Slutligen har vi implementerat ett verktyg för att analysera hur resultaten från funktionerna varierar efter valet av parametrar. Detta gör att man systematiskt kan bestämma vilka parametervärden som bör väljas för att garantera bra resultat samtidigt som exekveringstid hålls nere. Våra resultat visar att med våra förbättringar sänkes exekveringstiden med en faktor av omkring nio och förutsägelseförmågorna höjdes med en faktor av tre. Vi hoppas att vårt arbete kan leda till säkrare föutsägelser och vilket i sin tur kanske leder till en fredligare värld.

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MACHIRAJU, SIRISHA. "SPACE ALLOCATION FOR MATERIALIZED VIEWS AND INDEXES USING GENETIC ALGORITHMS." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1029435112.

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Mami, Imene. "A Declarative Approach to Modeling and Solving the View Selection Problem." Thesis, Montpellier 2, 2012. http://www.theses.fr/2012MON20194/document.

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La matérialisation de vues est une technique très utilisée dans les systèmes de gestion bases de données ainsi que dans les entrepôts de données pour améliorer les performances des requêtes. Elle permet de réduire de manière considérable le temps de réponse des requêtes en pré-calculant des requêtes coûteuses et en stockant leurs résultats. De ce fait, l'exécution de certaines requêtes nécessite seulement un accès aux vues matérialisées au lieu des données sources. En contrepartie, la matérialisation entraîne un surcoût de maintenance des vues. En effet, les vues matérialisées doivent être mises à jour lorsque les données sources changent afin de conserver la cohérence et l'intégrité des données. De plus, chaque vue matérialisée nécessite également un espace de stockage supplémentaire qui doit être pris en compte au moment de la sélection. Le problème de choisir quelles sont les vues à matérialiser de manière à réduire les coûts de traitement des requêtes étant donné certaines contraintes tel que l'espace de stockage et le coût de maintenance, est connu dans la littérature sous le nom du problème de la sélection de vues. Trouver la solution optimale satisfaisant toutes les contraintes est un problème NP-complet. Dans un contexte distribué constitué d'un ensemble de noeuds ayant des contraintes de ressources différentes (CPU, IO, capacité de l'espace de stockage, bande passante réseau, etc.), le problème de la sélection des vues est celui de choisir un ensemble de vues à matérialiser ainsi que les noeuds du réseau sur lesquels celles-ci doivent être matérialisées de manière à optimiser les coût de maintenance et de traitement des requêtes.Notre étude traite le problème de la sélection de vues dans un environnement centralisé ainsi que dans un contexte distribué. Notre objectif est de fournir une approche efficace dans ces contextes. Ainsi, nous proposons une solution basée sur la programmation par contraintes, connue pour être efficace dans la résolution des problèmes NP-complets et une méthode puissante pour la modélisation et la résolution des problèmes d'optimisation combinatoire. L'originalité de notre approche est qu'elle permet une séparation claire entre la formulation et la résolution du problème. A cet effet, le problème de la sélection de vues est modélisé comme un problème de satisfaction de contraintes de manière simple et déclarative. Puis, sa résolution est effectuée automatiquement par le solveur de contraintes. De plus, notre approche est flexible et extensible, en ce sens que nous pouvons facilement modéliser et gérer de nouvelles contraintes et mettre au point des heuristiques pour un objectif d'optimisation.Les principales contributions de cette thèse sont les suivantes. Tout d'abord, nous définissons un cadre qui permet d'avoir une meilleure compréhension des problèmes que nous abordons dans cette thèse. Nous analysons également l'état de l'art des méthodes de sélection des vues à matérialiser en en identifiant leurs points forts ainsi que leurs limites. Ensuite, nous proposons une solution utilisant la programmation par contraintes pour résoudre le problème de la sélection de vues dans un contexte centralisé. Nos résultats expérimentaux montrent notre approche fournit de bonnes performances. Elle permet en effet d'avoir le meilleur compromis entre le temps de calcul nécessaire pour la sélection des vues à matérialiser et le gain de temps de traitement des requêtes à réaliser en matérialisant ces vues. Enfin, nous étendons notre approche pour résoudre le problème de la sélection de vues à matérialiser lorsque celui-ci est étudié sous contraintes de ressources multiples dans un contexte distribué. A l'aide d'une évaluation de performances extensive, nous montrons que notre approche fournit des résultats de qualité et fiable
View selection is important in many data-intensive systems e.g., commercial database and data warehousing systems to improve query performance. View selection can be defined as the process of selecting a set of views to be materialized in order to optimize query evaluation. To support this process, different related issues have to be considered. Whenever a data source is changed, the materialized views built on it have to be maintained in order to compute up-to-date query results. Besides the view maintenance issue, each materialized view also requires additional storage space which must be taken into account when deciding which and how many views to materialize.The problem of choosing which views to materialize that speed up incoming queries constrained by an additional storage overhead and/or maintenance costs, is known as the view selection problem. This is one of the most challenging problems in data warehousing and it is known to be a NP-complete problem. In a distributed environment, the view selection problem becomes more challenging. Indeed, it includes another issue which is to decide on which computer nodes the selected views should be materialized. The view selection problem in a distributed context is now additionally constrained by storage space capacities per computer node, maximum global maintenance costs and the communications cost between the computer nodes of the network.In this work, we deal with the view selection problem in a centralized context as well as in a distributed setting. Our goal is to provide a novel and efficient approach in these contexts. For this purpose, we designed a solution using constraint programming which is known to be efficient for the resolution of NP-complete problems and a powerful method for modeling and solving combinatorial optimization problems. The originality of our approach is that it provides a clear separation between formulation and resolution of the problem. Indeed, the view selection problem is modeled as a constraint satisfaction problem in an easy and declarative way. Then, its resolution is performed automatically by the constraint solver. Furthermore, our approach is flexible and extensible, in that it can easily model and handle new constraints and new heuristic search strategies for optimization purpose. The main contributions of this thesis are as follows. First, we define a framework that enables to have a better understanding of the problems we address in this thesis. We also analyze the state of the art in materialized view selection to review the existing methods by identifying respective potentials and limits. We then design a solution using constraint programming to address the view selection problem in a centralized context. Our performance experimentation results show that our approach has the ability to provide the best balance between the computing time to be required for finding the materialized views and the gain to be realized in query processing by materializing these views. Our approach will also guarantee to pick the optimal set of materialized views where no time limit is imposed. Finally, we extend our approach to provide a solution to the view selection problem when the latter is studied under multiple resource constraints in a distributed context. Based on our extensive performance evaluation, we show that our approach outperforms the genetic algorithm that has been designed for a distributed setting

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Brigo, Matteo <1984&gt. "Cost Effective Semi-Automatic Algorithm for Materialized Views Selection in Data Warehousing in distribuite environment." Master's Degree Thesis, Università Ca' Foscari Venezia, 2016. http://hdl.handle.net/10579/8372.

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L'analisi dei dati attraverso un sistema datawarehouse è sempre più presente e necessaria per permettere alle aziende una corretta politica decisionale. Con l'aumentare della quantità di informazioni presenti nei sistemi informativi è cruciale concentrarsi sulla ottimizzazione delle query per il recupero di informazioni dai sistemi aziendali, inoltre sempre più spesso le aziende dispongono di sistemi distribuiti eterogenei. Scopo di questa tesi è proporre un metodo per ottimizzare la velocità di reperimento delle informazioni, attraverso l'uso di viste materializzate, tenendo conto dei vincoli spaziali e della possibilità di avere sistemi con velocità di calcolo non omogenee. Per far ciò abbiamo dapprima analizzato alcuni algoritmi già presenti in letteratura, concentrandoci su pregi e difetti, in secondo luogo abbiamo presentato una versione modificata di un algoritmo per tener conto dei vincoli aggiuntivi da noi premessi. Infine abbiamo dato un esempio dell'algoritmo proposto e ne abbiamo confrontato il risultato con gli altri algoritmi descritti.

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Katsifodimos, Asterios. "Scalable view-based techniques for web data : algorithms and systems." Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00870456.

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XML was recommended by W3C in 1998 as a markup language to be used by device- and system-independent methods of representing information. XML is nowadays used as a data model for storing and querying large volumes of data in database systems. In spite of significant research and systems development, many performance problems are raised by processing very large amounts of XML data. Materialized views have long been used in databases to speed up queries. Materialized views can be seen as precomputed query results that can be re-used to evaluate (part of) another query, and have been a topic of intensive research, in particular in the context of relational data warehousing. This thesis investigates the applicability of materialized views techniques to optimize the performance of Web data management tools, in particular in distributed settings, considering XML data and queries. We make three contributions.We first consider the problem of choosing the best views to materialize within a given space budget in order to improve the performance of a query workload. Our work is the first to address the view selection problem for a rich subset of XQuery. The challenges we face stem from the expressive power and features of both the query and view languages and from the size of the search space of candidate views to materialize. While the general problem has prohibitive complexity, we propose and study a heuristic algorithm and demonstrate its superior performance compared to the state of the art.Second, we consider the management of large XML corpora in peer-to-peer networks, based on distributed hash tables (or DHTs, in short). We consider a platform leveraging distributed materialized XML views, defined by arbitrary XML queries, filled in with data published anywhere in the network, and exploited to efficiently answer queries issued by any network peer. This thesis has contributed important scalability oriented optimizations, as well as a comprehensive set of experiments deployed in a country-wide WAN. These experiments outgrow by orders of magnitude similar competitor systems in terms of data volumes and data dissemination throughput. Thus, they are the most advanced in understanding the performance behavior of DHT-based XML content management in real settings.Finally, we present a novel approach for scalable content-based publish/subscribe (pub/sub, in short) in the presence of constraints on the available computational resources of data publishers. We achieve scalability by off-loading subscriptions from the publisher, and leveraging view-based query rewriting to feed these subscriptions from the data accumulated in others. Our main contribution is a novel algorithm for organizing subscriptions in a multi-level dissemination network in order to serve large numbers of subscriptions, respect capacity constraints, and minimize latency. The efficiency and effectiveness of our algorithm are confirmed through extensive experiments and a large deployment in a WAN.

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Karanasos, Konstantinos. "View-Based techniques for the efficient management of web data." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00755328.

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Data is being published in digital formats at very high rates nowadays. A large share of this data has complex structure, typically organized as trees (Web documents such as HTML and XML being the most representative) or graphs (in particular, graph-structured Semantic Web databases, expressed in RDF). There is great interest in exploiting such complex data, whether in an Open Data access model or within companies owning it, and efficiently doing so for large data volumes remains challenging. Materialized views have long been used to obtain significant performance improvements when processing queries. The principle is that a view stores pre-computed results that can be used to evaluate (possibly part of) a query. Adapting materialized view techniques to the Web data setting we consider is particularly challenging due to the structural and semantic complexity of the data. This thesis tackles two problems in the broad context of materialized view-based management of Web data. First, we focus on the problem of view selection for RDF query workloads. We present a novel algorithm, which, based on a query workload, proposes the most appropriate views to be materialized in the database, in order to minimize the combined cost of query evaluation, view maintenance and view storage. Although RDF query workloads typically feature many joins, hampering the view selection process, our algorithm scales to hundreds of queries, a number unattained by existing approaches. Furthermore, we propose new techniques to account for the implicit data that can be derived by the RDF Schemas and which further complicate the view selection process. The second contribution of our work concerns query rewriting based on materialized XML views. We start by identifying an expressive dialect of XQuery, corresponding to tree patterns with value joins, and study some important properties for these queries, such as containment and minimization. Based on these notions, we consider the problem of finding minimal equivalent rewritings of a query expressed in this dialect, using materialized views expressed in the same dialect, and provide a sound and complete algorithm for that purpose. Our work extends the state of the art by allowing each pattern node to return a set of attributes, supporting value joins in the patterns, and considering rewritings which combine many views. Finally, we show how our view-based query rewriting algorithm can be applied in a distributed setting, in order to efficiently disseminate corpora of XML documents carrying RDF annotations.

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Doubek, Petr. "Multi-view tracking and viewpoint selection." Konstanz : Hartung-Gorre Verlag, 2005. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=16071.

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Glenn-Applegate, Katherine. "Caregivers’ Preschool Selection Factors and Their Degree of Agency in Selecting High Quality Preschools." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306413949.

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Agrawal, Vikas R. "Data warehouse operational design : view selection and performance simulation." Toledo, Ohio : University of Toledo, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=toledo1104773641.

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Dissertation (Ph.D.)--University of Toledo, 2005.
Typescript. "Submitted as partial fulfillment of the requirements for the Doctor of Philosophy degree in Manufacturing Management and Engineering. " "A dissertation entitled"--at head of title. Title from title page of PDF document. Bibliography: p. 113-118.

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Chan, Ming-Yuen. "Transfer function design and view selection for angiographic visualization /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?COMP%202006%20CHAN.

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Zou, Li. "Global aggregate view selection in a peer warehousing system." Thesis, University of Ottawa (Canada), 2007. http://hdl.handle.net/10393/27946.

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Selecting views to materialize is one of the most important decisions to make when designing a data warehouse. In a peer data warehouse design, this problem is more difficult than in a centralized data warehouse design since the costs of global communication, data transfer, and data transformation between peers need to be additionally considered for getting the final integrated global query answers. The objective of our work is to select optimal sets of materialized aggregate views on different peers in a peer data warehousing system such that the total cost of answering the global queries posted on the given peer and maintaining the materialized views is minimized. In this thesis, we develop a theoretical framework for analyzing and solving the P2P global materialized view (GMV) selection problem. We extend the concepts of Expression AND-DAG, query aggregation lattice, and cost model defined on centralized data warehouses to the peer data warehousing semantics. In our problem scope, P2P Expression AND-DAG and P2P query aggregation lattice are constructed dynamically. In our cost model, we take the data transfer costs between peers and global materialized view maintenance costs into consideration. Then we extend an existing centralized view selection greedy algorithm to solve our P2P view selection problem. We assume that peer data warehouse dimensions are consistent throughout the whole system. We also assume that there is only one instance of the P2P GMV selection algorithm executing in the P2P system. Finally, we simulate the P2P view selection algorithm. The simulation experiment results show that the query frequencies and the update frequencies of materialized views, as well as the data transfer rate have critical impacts on the final view selection results. Moreover, the longest path of the P2P network, the number of granularity levels in the global dimension lattice, and the number of data warehouse dimensions affect the P2P view selection algorithm processing time and the minimum combination cost of answering global queries and maintaining the materialized views.

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AGRAWAL, VIKAS R. "Data Warehouse Operational Design: View Selection and Performance Simulation." University of Toledo / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1104773641.

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Boarman, McKaila J. S. "Trade-offs and Temporal Variation in Predator-Mediated Natural Selection and Sexual Selection on the Wings of the Damselfly Calopteryx splendens." Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1491746850419119.

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Meng, Xiaohong. "A data warehouse view selection scheme to accommodate dimension hierarchies." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0010/MQ52611.pdf.

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Wu, Lan. "Multi-view hockey tracking with trajectory smoothing and camera selection." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2402.

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We address the problem of multi-view multi-target tracking using multiple stationary cameras in the application of hockey tracking and test the approach with data from two cameras. The system is based on the previous work by Okuma et al. [50]. We replace AdaBoost detection with blob detection in both image coordinate systems after background subtraction. The sets of blob-detection results are then mapped to the rink coordinate system using a homography transformation. These observations are further merged into the final detection result which will be incorporated into the particle filter. In addition, we extend the particle filter to use multiple observation models, each corresponding to a view. An observation likelihood and a reference color model are also maintained for each player in each view and are updated only when the player is not occluded in that view. As a result of the expanded coverage range and multiple perspectives in the multi-view tracking, even when the target is occluded in one view, it still can be tracked as long as it is visible from another view. The multi-view tracking data are further processed by trajectory smoothing using the Maximum a posteriori smoother. Finally, automatic camera selection is performed using the Hidden Markov Model to create personalized video programs.

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Caperna, Carolyn Grace. "THE BOOK SELECTION PROCESS OF THIRD GRADE STUDENTS DURING LIBRARY." Bowling Green State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1174398868.

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MIO, CORRADO. "A POWER INDEX BASED FRAMEWORKFOR FEATURE SELECTION PROBLEMS." Doctoral thesis, Università degli Studi di Milano, 2020. http://hdl.handle.net/2434/709580.

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One of the most challenging tasks in the Machine Learning context is the feature selection. It consists in selecting the best set of features to use in the training and prediction processes. There are several benefits from pruning the set of actually operational features: the consequent reduction of the computation time, often a better quality of the prediction, the possibility to use less data to create a good predictor. In its most common form, the problem is called single-view feature selection problem, to distinguish it from the feature selection task in Multi-view learning. In the latter, each view corresponds to a set of features and one would like to enact feature selection on each view, subject to some global constraints. A related problem in the context of Multi-View Learning, is Feature Partitioning: it consists in splitting the set of features of a single large view into two or more views so that it becomes possible to create a good predictor based on each view. In this case, the best features must be distributed between the views, each view should contain synergistic features, while features that interfere disruptively must be placed in different views. In the semi-supervised multi-view task known as Co-training, one requires also that each predictor trained on an individual view is able to teach something to the other views: in classification tasks for instance, one view should learn to classify unlabelled examples based on the guess provided by the other views. There are several ways to address these problems. A set of techniques is inspired by Coalitional Game Theory. Such theory defines several useful concepts, among which two are of high practical importance: the concept of power index and the concept of interaction index. When used in the context of feature selection, they take the following meaning: the power index is a (context-dependent) synthesis measure of the prediction’s capability of a feature, the interaction index is a (context-dependent) synthesis measure of the interaction (constructive/disruptive interference) between two features: it can be used to quantify how the collaboration between two features enhances their prediction capabilities. An important point is that the powerindex of a feature is different from the predicting power of the feature in isolation: it takes into account, by a suitable averaging, the context, i.e. the fact that the feature is acting, together with other features, to train a model. Similarly, the interaction index between two features takes into account the context, by suitably averaging the interaction with all the other features. In this work we address both the single-view and the multi-view problems as follows. The single-view feature selection problem, is formalized as the problem of maximization of a pseudo-boolean function, i.e. a real valued set function (that maps sets of features into a performance metric). Since one has to enact a search over (a considerable portion of) the Boolean lattice (without any special guarantees, except, perhaps, positivity) the problem is in general NP-hard. We address the problem producing candidate maximum coalitions through the selection of the subset of features characterized by the highest power indices and using the coalition to approximate the actual maximum. Although the exact computation of the power indices is an exponential task, the estimates of the power indices for the purposes of the present problem can be achieved in polynomial time. The multi-view feature selection problem is formalized as the generalization of the above set-up to the case of multi-variable pseudo-boolean functions. The multi-view splitting problem is formalized instead as the problem of maximization of a real function defined over the partition lattice. Also this problem is typically NP-hard. However, candidate solutions can be found by suitably partitioning the top power-index features and keeping in different views the pairs of features that are less interactive or negatively interactive. The sum of the power indices of the participating features can be used to approximate the prediction capability of the view (i.e. they can be used as a proxy for the predicting power). The sum of the feature pair interactivity across views can be used as proxy for the orthogonality of the views. Also the capability of a view to pass information (to teach) to other views, within a co-training procedure can benefit from the use of power indices based on a suitable definition of information transfer (a set of features { a coalition { classifies examples that are subsequently used in the training of a second set of features). As to the feature selection task, not only we demonstrate the use of state of the art power index concepts (e.g. Shapley Value and Banzhaf along the 2lines described above Value), but we define new power indices, within the more general class of probabilistic power indices, that contains the Shapley and the Banzhaf Values as special cases. Since the number of features to select is often a predefined parameter of the problem, we also introduce some novel power indices, namely k-Power Index (and its specializations k-Shapley Value, k-Banzhaf Value): they help selecting the features in a more efficient way. For the feature partitioning, we use the more general class of probabilistic interaction indices that contains the Shapley and Banzhaf Interaction Indices as members. We also address the problem of evaluating the teaching ability of a view, introducing a suitable teaching capability index. The last contribution of the present work consists in comparing the Game Theory approach to the classical Greedy Forward Selection approach for feature selection. In the latter the candidate is obtained by aggregating one feature at time to the current maximal coalition, by choosing always the feature with the maximal marginal contribution. In this case we show that in typical cases the two methods are complementary, and that when used in conjunction they reduce one another error in the estimate of the maximum value. Moreover, the approach based on game theory has two advantages: it samples the space of all possible features’ subsets, while the greedy algorithm scans a selected subspace excluding totally the rest of it, and it is able, for each feature, to assign a score that describes a context-aware measure of importance in the prediction process.

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Borrenpohl, Daniel. "Genomic selection can replace phenotypic selection in early generation wheat breeding." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1562957699157873.

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Ballinger, Keli M. "The role of predominant world view in relation to coping strategy selection." Virtual Press, 1998. http://liblink.bsu.edu/uhtbin/catkey/1074550.

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Hylock, Ray Hales. "Beyond relational: a database architecture and federated query optimization in a multi-modal healthcare environment." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/2526.

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Over the past thirty years, clinical research has benefited substantially from the adoption of electronic medical record systems. As deployment has increased, so too has the number of researchers seeking to improve the overall analytical environment by way of tools and models. Although much work has been done, there are still many uninvestigated areas; two of which are explored in this dissertation. The first pertains to the physical storage of the data itself. There are two generally accepted storage models: relational and entity-attribute-value (EAV). For clinical data, EAV systems are preferred due to their natural way of managing many-to-many relationships, sparse attributes, and dynamic processes along with minimal conversion effort and reduction in federation complexities. However, the relational database management systems on which they are implemented, are not intended to organize and retrieve data in this format; eroding their performance gains. To combat this effect, we present the foundation for an EAV Database Management System (EDBMS). We discuss data conversion methodologies, formulate the requisite metadata and partitioned type-sensing index structures, and provide detailed runtime and experimental analysis with five extant methods. Our results show that the prototype, EAVDB, reduces space and conversion requirements while enhancing overall query performance. The second topic concerns query performance in a federated environment. One method used to decrease query execution time, is to pre-compute and store "beneficial" queries (views). The View Selection Problem (VSP) identifies these views subject to resource constraints. A federated model, however, has yet to be developed. In this dissertation, we submit three advances in view materialization. First, a more robust optimization function, the Minimum-Maintenance View Selection Problem (MMVSP), is derived by combining existing approaches. Second, the Federated View Selection Problem (FVSP), built upon the MMVSP, and federated data cube lattice are formalized. The FVSP allows for multiple querying nodes, partial and full materialization, and data propagation constriction. The latter two are shown to greatly reduce the overall number of valid solutions within the solution space and thus a novel, multi-tiered approach is given. Lastly, EAV materialization, which is introduced in this dissertation, is incorporated into an expanded, multi-modal variant of the FVSP. As models and heuristics for both the federated and EAV VSP, to the best of our knowledge, do not exist, this research defines two new branches of data warehouse optimization. Coupled with our EDBMS design, this dissertation confronts two main challenges associated with clinical data warehousing and federation.

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Chang, Christopher S. "Indecision in Employee Selection." Bowling Green State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1381750837.

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Dey, Tanujit. "Prediction and Variable Selection." Cleveland, Ohio : Case Western Reserve University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1212581055.

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Van, der Merwe Gerda. "The construct validity of the First View for selection purposes in South Africa." Diss., Pretoria : [s.n.], 2005. http://upetd.up.ac.za/thesis/available/etd-02272006-112454.

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Thesis (M.Com.(Human Resources Management)) - University of Pretoria, 2005.
Abstract in English and Afrikaans. Includes bibliographical references. Available on the Internet via the World Wide Web.

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Asgharzadeh, Talebi Zohreh. "Exact and Heuristic Methods for solving the View-Selection Problem for Aggregate Queries." NCSU, 2006. http://www.lib.ncsu.edu/theses/available/etd-05092006-123513/.

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In this thesis we present a formal study of the following view-selection problem: Given a set of queries, a database, and an upper bound on the amount of disk space that can be used to store materialized views, return definitions of views that, when materialized in the database, would reduce the evaluation costs of the queries. Optimizing the layout of stored data using view selection has a direct impact on the performance of the entire database system. At the same time, the optimization problem is intractable, even under natural restrictions on the types of queries of interest. We introduce an integer-programming model to obtain optimal solutions for the view-selection problem for aggregate queries on data warehouses. Through a computational experiment we show that this model can be used to solve realistic-size instances of the problem. We also report the results of the post-optimality analysis that we performed to determine the impact of changing certain input characteristics on the optimal solution. We solve large instances by applying several methods of reducing the size of the search space. We compare our approach to the leading heuristic procedure in the field [20].

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Hossain, Mohammad, and Shuang Cao. "Influencing Factors on the Selection Process of Enterprise System(s) : A study on the client and vendor perspectives." Thesis, Jönköping University, Jönköping International Business School, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-146.

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Enterprise system (ES) is being considered an important phenomenon in the corporate use of information technology, enhancing organizational cross functional efficiency and effectiveness through the integration of all the information flowing through a company. The implementation and use of this system involve high expenditure and risk and it has a great impact in every aspect of an adopting organization. The wrong selection of this system would have an adverse effect on the company performance. So the selection of this system deserves considerable attention from the practitioner and researcher.

In this study, our objective is to identify the influencing factors on the ES selection process from the existing theory and investigate them in real life situation from the client and vendor’s perspectives.

To fulfil the first objective of the study, we have made a comprehensive review on ES literature and synthesized an integrated framework of influencing factors on the ES selection process. To fulfil the other objective, we have made a qualitative empirical study through multiple case study approach. To collect necessary in-depth information, we have used purposive sampling and general interview guide approach. The integrated framework has guided us in empirical study and the cross case analysis of empirical data has been performed on the basis of this framework from the view point of client and vendor.

The result of this study shows that there exists a good fit between client and vendor views about the influencing factors on the ES selection process, in spite of insignificant imbalance between them. The result also reveals that most of the influencing factors of integrated framework have been recognized both by client and vendor with some diversity. Three new influencing factors: geographical proximity, requirement specification and sales skill of vendor have emerged from the study.

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Taylor, Anna B. "A Study of Variable Selection Methods in Supersaturated Models." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1586963467541177.

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He, Xinming, Keith D. Brouthers, and Igor Filatotchev. "Resource-Based and Institutional Perspectives on Export Channel Selection and Export Performance." Sage, 2013. http://dx.doi.org/10.1177/0149206312445926.

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Exporting is a critically important strategy for firms to grow, yet research in this area has tended to ignore how firms can leverage resource-based capabilities to improve export performance. Building on the resource-based view and institutional theory, the authors develop a novel perspective to explain how a firm can improve export performance by aligning its export channel with its level of market orientation capabilities, contingent on the institutional distance between home and export markets. Using a unique database of Chinese exporters, the authors find that exporters with strong market orientation capabilities prefer hierarchical export channels, while those with weak market orientation capabilities prefer hybrid channels. The analysis also indicates that the institutional distance between China and the export market moderates this relation. Moreover, the authors find that aligning export channel choice with firm-level market orientation capabilities and institutional distance yields better export performance. (authors' abstract)

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You, Di. "Model Selection in Kernel Methods." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1322581224.

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KESKAR, HARSHAL S. "SUPPLIER SELECTION METRICS AND METHODOLOGY." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1085680712.

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Sarkar, Saurabh. "Feature Selection with Missing Data." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378194989.

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Miller, John Ora. "Efficient multinomial selection in simulation /." The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487943341529543.

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Han, Yuchen. "Bayesian Variable Selection Using Lasso." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1491775118610981.

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Gilbride, Timothy J. "Models for heterogeneous variable selection." Columbus, Ohio : Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1083591017.

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Thesis (Ph. D.)--Ohio State University, 2004.
Title from first page of PDF file. Document formatted into pages; contains xii, 138 p.; also includes graphics. Includes abstract and vita. Advisor: Greg M. Allenby, Dept. of Business Admnistration. Includes bibliographical references (p. 134-138).

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Yao, Yonggang. "Statistical Applications of Linear Programming for Feature Selection via Regularization Methods." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1222035715.

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Yousif, Ibrahim Abdelsalam. "Restricted selection index as applied to selection for body composition in Japanese quail (Coturnix coturnix japonica) /." The Ohio State University, 1992. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487777170407177.

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39

Wang, Cong. "Household Risky Assets: Selection And Allocation." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1204747467.

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Delaney, Michael B. "Selection Method and Judicial Background Characteristics." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1382372765.

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Goyal, Anushree. "A Framework for XML Index Selection." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384426003.

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Arledge, Christopher S. "Cosmological Model Selection and Akaike’s Criterion." Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1430478203.

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Rinehart, James S. "An activity dimension in teacher selection /." The Ohio State University, 1988. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487595712157055.

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Jia, Ning. "View-invariant feature selector and its application on gait recognition." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/94744/.

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The proliferation of the national-wide deployment of surveillance cameras and identity management systems has promoted the development of biometric systems. Gait as a behavioural biometric trait can be measured unobtrusively at a moderate distance, thus it is predominant in remote human tracking and identification tasks. The past two decades have witnessed a considerable development of gait recognition systems. Yet there are challenges that confine the practical application of gait analysis. The motivation of our work is to identify the problems and find corresponding solutions to explore the potentials of gait recognition and promote its applicability in open-world scenarios. Gait recognition systems use human profile as features, while the appearance of human profile, also known as silhouette, can be affected in various manners. For example, clothing changes the shape of torso (coat) or legs (skirt); carrying bag attaches extra region to the silhouette; walking surface or speed variation changes the appearance of legs. On the other hand, camera viewpoint variation changes the shape of both the upper and lower body, while segmentation errors may cause massive corruption of the gait features. We summarise them into two categories: partial interference and holistic deformation. The former has been well addressed by existing literatures. The holistic deformation on gait silhouette results in large intra-class variation, and we notice that the performance of conventional approaches decreases under such circumstance. Thus our work focus mostly on the latter challenge. Accordingly, we propose ViFS, an automatic feature selection approach that seeks for the optimal representation features from gallery set, and evaluate its performance under various conditions. We find that ViFS minimises the intra-class variation between gallery and probe data, and by introducing proper feature enhancers, we can further reduce the number of holistic deformation modalities required in the gallery set. We test the proposed method on public dataset that contains viewpoint variations, and the matching accuracy has achieved 99.1% on CASIA Dataset B and 97.7% on OU-ISIR Large Population Dataset. The formulation and discussion are presented in Chapter 3. The success of Convolutional Neural Network (CNN) based methods in image classification field has drawn attention from researchers. Recently a large number of literatures have covered the application of CNN in computer vision tasks, including face and gait recognition in the biometrics field. CNN has much greater discriminant learning ability in the highly non-linear space. Thus we merge CNN feature maps with the proposed ViFS approach, which achieves the state-of-the-art performance on view-invariant gait recognition problem. The methodology and results are presented in Chapter 4. Among the holistic deformation challenge, the silhouette quality issue is seldom addressed, while no published dataset concerns with the influence of segmentation quality on gait recognition algorithms. We create a dataset that contains silhouettes with six different segmentation qualities in both gallery and probe set, and evaluated the conventional methods as well as the proposed ViFS approach on this dataset. It is proved that ViFS based framework and its extension outperforms the conventional methods by 8%-10%, which further indicates the effectiveness of ViFS based framework on gait holistic deformation challenge. This work is presented in Chapter 5. This thesis aims at tackling the gait silhouette holistic deformation challenge, and ViFS based frameworks are proposed to achieve robust recognition performance. We evaluate the effect of different feature enhancers for ViFS, and find out that the discriminant power of CNN feature maps is much more powerful than subspace learning methods (3% higher accuracy under same conditions), thus it requires less gallery data to achieve deformation-invariant recognition.

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Ruiz, Altisent Marc. "Advanced illumination and view-selection techniques for volume rendering and its application to medical imaging." Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/371154.

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Volume visualization is a method of extracting information from volumetric data using interactive graphics. Volume visualization aims to assist visual interpretation of data by creating three-dimensional models that reproduce real objects with sufficient detail and speed to support interactive manipulation. Illustrative rendering enhances the perception of features in a volume. Volume rendering has two major goals: to obtain high quality images in real time, and to determine how to explore volume datasets in an effective way. In this thesis we advance in these two lines. We propose several methods to approximate global illumination with low computational cost, permitting realistic and illustrative rendering. We also present a method to automatically define transfer functions given a target distribution. In addition, we introduce a method to automatize the creation of exploded views. Finally, we explore techniques to select the best viewpoints for a volume. Several of our contributions are based on information theory.
La visualització de volums és un mètode per extreure informació de dades volumètriques mitjançant imatges interactives. L’objectiu és assistir la interpretació visual de dades creant models tridimensionals que reprodueixen objectes reals amb suficient detall i velocitat per permetre’n la manipulació interactivament. La visualització il·lustrativa millora la percepció de les característiques d'un volum. La visualització de volums té dos objectius principals: obtenir imatges d’alta qualitat en temps real, i determinar com explorar volums d'una manera efectiva. En aquesta tesi avancem en aquestes dues línies. Proposem diversos mètodes per aproximar la il·luminació global amb baix cost computacional, permetent la visualització realista i il·lustrativa. També presentem un mètode per definir automàticament funcions de transferència donada una distribució objectiu. A més, presentem un mètode per automatitzar la creació d’exploded views. Finalment, explorem tècniques per seleccionar els millors punts de vista d’un volum. Diverses de les contribucions estan basades en la teoria de la informació.

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Nesnidol, Samantha A. "Public Sector Perceptions of Unproctored Internet Testing." Bowling Green State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1478170694534844.

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Hang, Hongli. "TO USE OR NOT TO USE: A CHOICE OF SELECTION METHODS FOR INTERNSHIPS IN U.S. FIRMS." Kent State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=kent1556790505485288.

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Yousef, Mohammed A. "Two-Stage SCAD Lasso for Linear Mixed Model Selection." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1558431514460879.

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Ponangi, Preethi Vinayak. "Cognitive Cyber Weapon Selection Tool Empirical Evaluation." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1303229011.

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Subedi, Bijay. "Material Selection for Spray Injection Patching Method." University of Akron / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=akron1449231554.

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Dissertations / Theses on the topic 'Views selection'

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