Similarity queries: Their conceptual evaluation, transformations, and processing

Yasin Silva, Walid G. Aref, Per Ake Larson, Spencer S. Pearson, Mohamed H. Ali

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


Many application scenarios can significantly benefit from the identification and processing of similarities in the data. Even though some work has been done to extend the semantics of some operators, for example join and selection, to be aware of data similarities, there has not been much study on the role and implementation of similarity-aware operations as first-class database operators. Furthermore, very little work has addressed the problem of evaluating and optimizing queries that combine several similarity operations. The focus of this paper is the study of similarity queries that contain one or multiple first-class similarity database operators such as Similarity Selection, Similarity Join, and Similarity Group-by. Particularly, we analyze the implementation techniques of several similarity operators, introduce a consistent and comprehensive conceptual evaluation model for similarity queries, and present a rich set of transformation rules to extend cost-based query optimization to the case of similarity queries.

Original languageEnglish (US)
Pages (from-to)395-420
Number of pages26
JournalVLDB Journal
Issue number3
StatePublished - Jun 2013


  • Conceptual evaluation
  • Query processing
  • Query transformations
  • Similarity queries

ASJC Scopus subject areas

  • Information Systems
  • Hardware and Architecture


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