Range query estimation with data skewness for top-k retrieval

Anteneh Ayanso; Paulo B. Goes; Kumar Mehta

doi:10.1016/j.dss.2013.09.005

Range query estimation with data skewness for top-k retrieval

Anteneh Ayanso, Paulo B. Goes, Kumar Mehta

Management Information Systems

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	258-273
Number of pages	16
Journal	Decision Support Systems
Volume	57
Issue number	1
DOIs	https://doi.org/10.1016/j.dss.2013.09.005
State	Published - Jan 2014

Keywords

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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10.1016/j.dss.2013.09.005

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abstract = "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.",

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AB - 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.

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Range query estimation with data skewness for top-k retrieval

Abstract

Keywords

ASJC Scopus subject areas

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