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Selectivity estimation for exclusive query translation in deep web data integration

  • Renmin University of China
  • Jiangsu Normal University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In Deep Web data integration, some Web database interfaces express exclusive predicates of the form Q e = Pi(Pi∈ P1, P2, . . . , Pm), which permits only one predicate to be selected at a time. Accurately and efficiently estimating the selectivity of each Q e is of critical importance to optimal query translation. In this paper, we mainly focus on the selectivity estimation on infinite-value attribute which is more difficult than that on key attribute and categorical attribute. Firstly, we compute the attribute correlation and retrieve approximate random attribute-level samples through submitting queries on the least correlative attribute to the actual Web database. Then we estimate Zipf equation based on the word rank of the sample and the actual selectivity of several words from the actual Web database. Finally, the selectivity of any word on the infinite-value attribute can be derived by the Zipf equation. An experimental evaluation of the proposed selectivity estimation method is provided and experimental results are highly accurate.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 14th International Conference, DASFAA 2009, Proceedings
Pages595-600
Number of pages6
DOIs
StatePublished - 2009
Event14th International Conference on Database Systems for Advanced Applications, DASFAA 2009 - Brisbane, QLD, Australia
Duration: Apr 21 2009Apr 23 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5463

Conference

Conference14th International Conference on Database Systems for Advanced Applications, DASFAA 2009
Country/TerritoryAustralia
CityBrisbane, QLD
Period04/21/0904/23/09

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