Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases

Detalhes bibliográficos
Autor(a) principal: Oliveira, Péricles Silva de
Data de Publicação: 2017
Outros Autores: http://lattes.cnpq.br/9559422309114150
Tipo de documento: Tese
Idioma: por
Título da fonte: Biblioteca Digital de Teses e Dissertações da UFAM
Texto Completo: http://tede.ufam.edu.br/handle/tede/5806
Resumo: Sem resumo.
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spelling Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational DatabasesKeyword-searchMatch graphRelational databaseRanking Candidate networksCIÊNCIAS EXATAS E DA TERRA: CIÊNCIA DA COMPUTAÇÃOSem resumo.Several systems proposed for processing keyword queries over relational databases rely on the generation and evaluation of Candidate Networks (CNs), i.e., networks of joined database relations that, when processed as SQL queries, provide a relevant answer to the input keyword query. Although the evaluation of CNs has been extensively addressed in the literature, problems related to efficiently generating meaningful CNs have received much less attention. To generate useful CNs is necessary to automatically locating, given a handful of keywords, relations in the database that may contain relevant pieces of information, and determining suitable ways of joining these relations to satisfy the implicit information need expressed by a user when formulating her query. In this thesis, we present two main contributions related to the processing of Candidate Networks. As our first contribution, we present a novel approach for generating CNs, in which possible matchings of the query in database are efficiently enumerated at first. These query matches are then used to guide the CN generation process, avoiding the exhaustive search procedure used by current state-of-art approaches. We show that our approach allows the generation of a compact set of CNs that leads to superior quality answers, and that demands less resources in terms of processing time and memory. As our second contribution, we initially argue that the number of possible Candidate Networks that can be generated by any algorithm is usually very high, but that, in fact, only very few of them produce answers relevant to the user and are indeed worth processing. Thus, there is no point in wasting resources processing useless CNs. Then, based on such an argument, we present an algorithm for ranking CNs, based on their probability of producing relevant answers to the user. This relevance is estimated based on the current state of the underlying database using a probabilistic Bayesian model we have developed. By doing so we are able do discard a large number of CNs, ultimately leading to better results in terms of quality and performance. Our claims and proposals are supported by a comprehensive set of experiments we carried out using several query sets and datasets used in previous related work and whose results we report and analyse here.Universidade Federal do AmazonasInstituto de ComputaçãoBrasilUFAMPrograma de Pós-graduação em InformáticaSilva, Altigran Soares dahttp://lattes.cnpq.br/3405503472010994Oliveira, Péricles Silva dehttp://lattes.cnpq.br/95594223091141502017-08-22T19:40:44Z2017-04-28info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfOLIVEIRA, Péricles Silva de. Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases. 2017. 78 f. Tese (Doutorado em Informática) - Universidade Federal do Amazonas, Manaus, 2017.http://tede.ufam.edu.br/handle/tede/5806porhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UFAMinstname:Universidade Federal do Amazonas (UFAM)instacron:UFAM2017-08-23T05:04:04Zoai:https://tede.ufam.edu.br/handle/:tede/5806Biblioteca Digital de Teses e Dissertaçõeshttp://200.129.163.131:8080/PUBhttp://200.129.163.131:8080/oai/requestddbc@ufam.edu.br||ddbc@ufam.edu.bropendoar:65922017-08-23T05:04:04Biblioteca Digital de Teses e Dissertações da UFAM - Universidade Federal do Amazonas (UFAM)false
dc.title.none.fl_str_mv Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
title Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
spellingShingle Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
Oliveira, Péricles Silva de
Keyword-search
Match graph
Relational database
Ranking Candidate networks
CIÊNCIAS EXATAS E DA TERRA: CIÊNCIA DA COMPUTAÇÃO
title_short Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
title_full Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
title_fullStr Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
title_full_unstemmed Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
title_sort Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases
author Oliveira, Péricles Silva de
author_facet Oliveira, Péricles Silva de
http://lattes.cnpq.br/9559422309114150
author_role author
author2 http://lattes.cnpq.br/9559422309114150
author2_role author
dc.contributor.none.fl_str_mv Silva, Altigran Soares da
http://lattes.cnpq.br/3405503472010994
dc.contributor.author.fl_str_mv Oliveira, Péricles Silva de
http://lattes.cnpq.br/9559422309114150
dc.subject.por.fl_str_mv Keyword-search
Match graph
Relational database
Ranking Candidate networks
CIÊNCIAS EXATAS E DA TERRA: CIÊNCIA DA COMPUTAÇÃO
topic Keyword-search
Match graph
Relational database
Ranking Candidate networks
CIÊNCIAS EXATAS E DA TERRA: CIÊNCIA DA COMPUTAÇÃO
description Sem resumo.
publishDate 2017
dc.date.none.fl_str_mv 2017-08-22T19:40:44Z
2017-04-28
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv OLIVEIRA, Péricles Silva de. Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases. 2017. 78 f. Tese (Doutorado em Informática) - Universidade Federal do Amazonas, Manaus, 2017.
http://tede.ufam.edu.br/handle/tede/5806
identifier_str_mv OLIVEIRA, Péricles Silva de. Generation and Ranking of Candidate Networks of Relations for Keyword Search over Relational Databases. 2017. 78 f. Tese (Doutorado em Informática) - Universidade Federal do Amazonas, Manaus, 2017.
url http://tede.ufam.edu.br/handle/tede/5806
dc.language.iso.fl_str_mv por
language por
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Amazonas
Instituto de Computação
Brasil
UFAM
Programa de Pós-graduação em Informática
publisher.none.fl_str_mv Universidade Federal do Amazonas
Instituto de Computação
Brasil
UFAM
Programa de Pós-graduação em Informática
dc.source.none.fl_str_mv reponame:Biblioteca Digital de Teses e Dissertações da UFAM
instname:Universidade Federal do Amazonas (UFAM)
instacron:UFAM
instname_str Universidade Federal do Amazonas (UFAM)
instacron_str UFAM
institution UFAM
reponame_str Biblioteca Digital de Teses e Dissertações da UFAM
collection Biblioteca Digital de Teses e Dissertações da UFAM
repository.name.fl_str_mv Biblioteca Digital de Teses e Dissertações da UFAM - Universidade Federal do Amazonas (UFAM)
repository.mail.fl_str_mv ddbc@ufam.edu.br||ddbc@ufam.edu.br
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