An indexing technique for similarity-based fuzzy object-oriented data model

Adnan Yazici, Çagri Ince, Murat Koyuncu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Fuzzy object-oriented data model is a fuzzy logic-based extension to object-oriented database model, which permits uncertain data to be explicitlyrepresented. One of the proposed fuzzy object-oriented database models based on similarity relations is the FOOD model. Several kinds of fuzziness are dealtwith in the FOOD model, including fuzziness between object/class and class/ superclass relations. The traditional index structures are inappropriate for theFOOD model for an efficient access to the objects with crisp or fuzzy values, since they are not efficient for processing both crisp and fuzzy queries. In thisstudy we propose a new index structure (the FOOD Index) dealing with different kinds of fuzziness in FOOD databases and supports multi-dimensional indexing. We describe how the FOOD Index supports various types of flexible queries and evaluate performance results of crisp, range, and fuzzy queries usingthe FOOD index.

Original languageEnglish
Title of host publicationFlexible Query Answering Systems
EditorsHenning Christiansen, Troels Andreasen, Mohand-Said Hacid, Henrik Legind Larsen
PublisherSpringer Verlag
Pages334-347
Number of pages14
ISBN (Print)3540221603, 9783540221609
DOIs
Publication statusPublished - 2004
Event6th International Conference on Flexible Query Answering Systems, FQAS 2004 - Lyon, France
Duration: Jun 24 2004Jun 26 2004

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume3055
ISSN (Print)0302-9743

Conference

Conference6th International Conference on Flexible Query Answering Systems, FQAS 2004
Country/TerritoryFrance
CityLyon
Period6/24/046/26/04

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

Fingerprint

Dive into the research topics of 'An indexing technique for similarity-based fuzzy object-oriented data model'. Together they form a unique fingerprint.

Cite this