Range query estimation with data skewness for top-k retrieval

Anteneh Ayanso, Paulo B. Goes, Kumar Mehta

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Top-k querying can significantly improve the performance of web-based business intelligence applications such as price comparison and product recommendation systems. Top-k retrieval involves finding a limited number of records in a relational database that are most similar to user-specified attribute-value pairs. This paper extends the cost-based query-mapping method for top-k retrieval by incorporating data skewness in range estimation. Experiments on real world and synthetic multi-attribute data sets show that incorporating data skewness provides a robust performance across different types of data sets, query sets, distance functions, and histograms.

Original languageEnglish (US)
Pages (from-to)258-273
Number of pages16
JournalDecision Support Systems
Issue number1
StatePublished - Jan 2014


  • Cost model
  • Query processing
  • Query-mapping
  • RDBMSs
  • Top-k query

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Information Systems and Management


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