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Article: Size-l Object summaries for relational keyword search

TitleSize-l Object summaries for relational keyword search
Authors
KeywordsComprehensive information
Data subjects
Exponential time
Keyword search
Search engines
Issue Date2011
PublisherVery Large Data Base (VLDB) Endowment Inc.. The Journal's web site is located at http://vldb.org/pvldb/index.html
Citation
Proceedings of the VLDB Endowment, 2011, v. 5 n. 3, p. 229-240 How to Cite?
AbstractA previously proposed keyword search paradigm produces, as a query result, a ranked list of Object Summaries (OSs). An OS is a tree structure of related tuples that summarizes all data held in a relational database about a particular Data Subject (DS). However, some of these OSs are very large in size and therefore unfriendly to users that initially prefer synoptic information before proceeding to more comprehensive information about a particular DS. In this paper, we investigate the effective and efficient retrieval of concise and informative OSs. We argue that a good size-l OS should be a stand-alone and meaningful synopsis of the most important information about the particular DS. More precisely, we define a size-l OS as a partial OS composed of l important tuples. We propose three algorithms for the efficient generation of size-l OSs (in addition to the optimal approach which requires exponential time). Experimental evaluation on DBLP and TPC-H databases verifies the effectiveness and efficiency of our approach. © 2011 VLDB Endowment.
Persistent Identifierhttp://hdl.handle.net/10722/165847
ISSN

 

DC FieldValueLanguage
dc.contributor.authorFakas, GJen_US
dc.contributor.authorCai, Zen_US
dc.contributor.authorMamoulis, Nen_US
dc.date.accessioned2012-09-20T08:24:31Z-
dc.date.available2012-09-20T08:24:31Z-
dc.date.issued2011en_US
dc.identifier.citationProceedings of the VLDB Endowment, 2011, v. 5 n. 3, p. 229-240en_US
dc.identifier.issn2150-8097-
dc.identifier.urihttp://hdl.handle.net/10722/165847-
dc.description.abstractA previously proposed keyword search paradigm produces, as a query result, a ranked list of Object Summaries (OSs). An OS is a tree structure of related tuples that summarizes all data held in a relational database about a particular Data Subject (DS). However, some of these OSs are very large in size and therefore unfriendly to users that initially prefer synoptic information before proceeding to more comprehensive information about a particular DS. In this paper, we investigate the effective and efficient retrieval of concise and informative OSs. We argue that a good size-l OS should be a stand-alone and meaningful synopsis of the most important information about the particular DS. More precisely, we define a size-l OS as a partial OS composed of l important tuples. We propose three algorithms for the efficient generation of size-l OSs (in addition to the optimal approach which requires exponential time). Experimental evaluation on DBLP and TPC-H databases verifies the effectiveness and efficiency of our approach. © 2011 VLDB Endowment.-
dc.languageengen_US
dc.publisherVery Large Data Base (VLDB) Endowment Inc.. The Journal's web site is located at http://vldb.org/pvldb/index.html-
dc.relation.ispartofProceedings of the VLDB Endowmenten_US
dc.subjectComprehensive information-
dc.subjectData subjects-
dc.subjectExponential time-
dc.subjectKeyword search-
dc.subjectSearch engines-
dc.titleSize-l Object summaries for relational keyword searchen_US
dc.typeArticleen_US
dc.identifier.emailMamoulis, N: nikos@cs.hku.hken_US
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.identifier.scopuseid_2-s2.0-84863730965-
dc.identifier.hkuros208286en_US
dc.identifier.volume5en_US
dc.identifier.issue3-
dc.identifier.spage229en_US
dc.identifier.epage240en_US
dc.publisher.placeUnited States-

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