Cardinality estimation for the optimization of queries on ontologies

E. Patrick Shironoshita, Michael T. Ryan, Mansur R. Kabuka

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

An effective, accurate algorithm for cardinality estimation of queries on ontology models of data is presented. The algorithm relies on the decomposition of queries into query pattern paths, where each path produces a set of values for each variable within the result form of the query. In order to estimate the total number of result set parameters for each path, a set of statistics is compiled on the properties of the ontology. Experimental analysis has shown that the algorithm produces estimates with high accuracy and with high correlation to actual values. Thus, this algorithm can be used as the cornerstone of an effective optimization strategy for queries on diverse, heterogeneous data sources modeled as ontologies.

Original languageEnglish
Pages (from-to)13-18
Number of pages6
JournalSIGMOD Record
Volume36
Issue number2
DOIs
StatePublished - Jun 1 2007

Fingerprint

Ontology
Statistics
Decomposition

Keywords

  • Cardinality estimation
  • Ontology
  • OWL
  • Query optimization
  • Semantic query
  • SPARQL

ASJC Scopus subject areas

  • Information Systems
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Cardinality estimation for the optimization of queries on ontologies. / Shironoshita, E. Patrick; Ryan, Michael T.; Kabuka, Mansur R.

In: SIGMOD Record, Vol. 36, No. 2, 01.06.2007, p. 13-18.

Research output: Contribution to journalArticle

Shironoshita, E. Patrick ; Ryan, Michael T. ; Kabuka, Mansur R. / Cardinality estimation for the optimization of queries on ontologies. In: SIGMOD Record. 2007 ; Vol. 36, No. 2. pp. 13-18.
@article{74f1daa3388c48d29fb86222735229d1,
title = "Cardinality estimation for the optimization of queries on ontologies",
abstract = "An effective, accurate algorithm for cardinality estimation of queries on ontology models of data is presented. The algorithm relies on the decomposition of queries into query pattern paths, where each path produces a set of values for each variable within the result form of the query. In order to estimate the total number of result set parameters for each path, a set of statistics is compiled on the properties of the ontology. Experimental analysis has shown that the algorithm produces estimates with high accuracy and with high correlation to actual values. Thus, this algorithm can be used as the cornerstone of an effective optimization strategy for queries on diverse, heterogeneous data sources modeled as ontologies.",
keywords = "Cardinality estimation, Ontology, OWL, Query optimization, Semantic query, SPARQL",
author = "Shironoshita, {E. Patrick} and Ryan, {Michael T.} and Kabuka, {Mansur R.}",
year = "2007",
month = "6",
day = "1",
doi = "10.1145/1328854.1328856",
language = "English",
volume = "36",
pages = "13--18",
journal = "SIGMOD Record",
issn = "0163-5808",
publisher = "Association for Computing Machinery (ACM)",
number = "2",

}

TY - JOUR

T1 - Cardinality estimation for the optimization of queries on ontologies

AU - Shironoshita, E. Patrick

AU - Ryan, Michael T.

AU - Kabuka, Mansur R.

PY - 2007/6/1

Y1 - 2007/6/1

N2 - An effective, accurate algorithm for cardinality estimation of queries on ontology models of data is presented. The algorithm relies on the decomposition of queries into query pattern paths, where each path produces a set of values for each variable within the result form of the query. In order to estimate the total number of result set parameters for each path, a set of statistics is compiled on the properties of the ontology. Experimental analysis has shown that the algorithm produces estimates with high accuracy and with high correlation to actual values. Thus, this algorithm can be used as the cornerstone of an effective optimization strategy for queries on diverse, heterogeneous data sources modeled as ontologies.

AB - An effective, accurate algorithm for cardinality estimation of queries on ontology models of data is presented. The algorithm relies on the decomposition of queries into query pattern paths, where each path produces a set of values for each variable within the result form of the query. In order to estimate the total number of result set parameters for each path, a set of statistics is compiled on the properties of the ontology. Experimental analysis has shown that the algorithm produces estimates with high accuracy and with high correlation to actual values. Thus, this algorithm can be used as the cornerstone of an effective optimization strategy for queries on diverse, heterogeneous data sources modeled as ontologies.

KW - Cardinality estimation

KW - Ontology

KW - OWL

KW - Query optimization

KW - Semantic query

KW - SPARQL

UR - http://www.scopus.com/inward/record.url?scp=35948993914&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=35948993914&partnerID=8YFLogxK

U2 - 10.1145/1328854.1328856

DO - 10.1145/1328854.1328856

M3 - Article

VL - 36

SP - 13

EP - 18

JO - SIGMOD Record

JF - SIGMOD Record

SN - 0163-5808

IS - 2

ER -