Querying web metadata: Native score management and text support in databases

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buir.contributor.authorUlusoy, Özgür
dc.citation.epage634en_US
dc.citation.issueNumber4en_US
dc.citation.spage581en_US
dc.citation.volumeNumber29en_US
dc.contributor.authorÖzsoyoǧlu, G.en_US
dc.contributor.authorAltingövde, I. S.en_US
dc.contributor.authorAl-Hamdani, A.en_US
dc.contributor.authorÖzel, S. A.en_US
dc.contributor.authorUlusoy, Özgüren_US
dc.contributor.authorÖzsoyoǧlu, Z. M.en_US
dc.date.accessioned2016-02-08T10:25:05Z
dc.date.available2016-02-08T10:25:05Zen_US
dc.date.issued2004en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractIn this article, we discuss the issues involved in adding a native score management system to object-relational databases, to be used in querying Web metadata (that describes the semantic content of Web resources). The Web metadata model is based on topics (representing entities), relationships among topics (called metalinks), and importance scores (sideway values) of topics and metalinks. We extend database relations with scoring functions and importance scores. We add to SQL score-management clauses with well-defined semantics, and propose the sidewayvalue algebra (SVA), to evaluate the extended SQL queries. SQL extensions and the SVA algebra are illustrated through two Web resources, namely, the DBLP Bibliography and the SIGMOD Anthology. SQL extensions include clauses for propagating input tuple importance scores to output tuples during query processing, clauses that specify query stopping conditions, threshold predicates (a type of approximate similarity predicates for text comparisons), and user-defined-function-based predicates. The propagated importance scores are then used to rank and return a small number of output tuples. The query stopping conditions are propagated to SVA operators during query processing. We show that our SQL extensions are well-defined, meaning that, given a database and a query Q, under any query processing scheme, the output tuples of Q and their importance scores stay the same. To process the SQL extensions, we discuss two sideway value algebra operators, namely, sideway value algebra join and topic closure, give their implementation algorithms, and report their experimental evaluations.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T10:25:05Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2004en_US
dc.identifier.doi10.1145/1042046.1042047en_US
dc.identifier.issn0362-5915
dc.identifier.issn1557-4644
dc.identifier.urihttp://hdl.handle.net/11693/24167en_US
dc.language.isoEnglishen_US
dc.publisherAssociation for Computing Machineryen_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/1042046.1042047en_US
dc.source.titleACM Transactions on Database Systemsen_US
dc.subjectScore management for Web applicationsen_US
dc.subjectExperimentationen_US
dc.subjectQueryingen_US
dc.subjectScore management for web applicationsen_US
dc.subjectSideway value algebra (SVA)en_US
dc.subjectAlgebraen_US
dc.subjectAlgorithmsen_US
dc.subjectDesignen_US
dc.subjectFormal languagesen_US
dc.subjectMetadataen_US
dc.subjectQuery languagesen_US
dc.subjectSemanticsen_US
dc.subjectDatabase systemsen_US
dc.titleQuerying web metadata: Native score management and text support in databasesen_US
dc.typeArticleen_US

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