Range query estimation with data skewness for top-k retrieval

Anteneh Ayanso, Paulo B Goes, Kumar Mehta

Research output: Contribution to journalArticle

2 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)258-273
Number of pages16
JournalDecision Support Systems
Volume57
Issue number1
DOIs
StatePublished - Jan 2014

Fingerprint

Competitive intelligence
Recommender systems
Information Storage and Retrieval
Intelligence
Costs
Experiments
Databases
Costs and Cost Analysis
Datasets
Skewness
Top-k
Query
World Wide Web
Experiment
Relational Database
Real World
Distance Function

Keywords

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

ASJC Scopus subject areas

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

Cite this

Range query estimation with data skewness for top-k retrieval. / Ayanso, Anteneh; Goes, Paulo B; Mehta, Kumar.

In: Decision Support Systems, Vol. 57, No. 1, 01.2014, p. 258-273.

Research output: Contribution to journalArticle

Ayanso, Anteneh ; Goes, Paulo B ; Mehta, Kumar. / Range query estimation with data skewness for top-k retrieval. In: Decision Support Systems. 2014 ; Vol. 57, No. 1. pp. 258-273.
@article{6142d81742ca48cc9343a2ff8a8a7dd8,
title = "Range query estimation with data skewness for top-k retrieval",
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.",
keywords = "Cost model, Query processing, Query-mapping, RDBMSs, Top-k query",
author = "Anteneh Ayanso and Goes, {Paulo B} and Kumar Mehta",
year = "2014",
month = "1",
doi = "10.1016/j.dss.2013.09.005",
language = "English (US)",
volume = "57",
pages = "258--273",
journal = "Decision Support Systems",
issn = "0167-9236",
publisher = "Elsevier",
number = "1",

}

TY - JOUR

T1 - Range query estimation with data skewness for top-k retrieval

AU - Ayanso, Anteneh

AU - Goes, Paulo B

AU - Mehta, Kumar

PY - 2014/1

Y1 - 2014/1

N2 - 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.

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.

KW - Cost model

KW - Query processing

KW - Query-mapping

KW - RDBMSs

KW - Top-k query

UR - http://www.scopus.com/inward/record.url?scp=84892373625&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84892373625&partnerID=8YFLogxK

U2 - 10.1016/j.dss.2013.09.005

DO - 10.1016/j.dss.2013.09.005

M3 - Article

AN - SCOPUS:84892373625

VL - 57

SP - 258

EP - 273

JO - Decision Support Systems

JF - Decision Support Systems

SN - 0167-9236

IS - 1

ER -