Ontology-Guided Change Detection to the Semantic Web Data

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The Semantic Web is envisioned as the next generation web in which data instances are enriched with metadata defined in ontologies to describe the meaning of its instances. In this paper, we present an approach that exploits ontologies in guiding the change detection to their data instances. Inference rules are identified based on the semantic relationships among concepts, properties and instances as well as their change behaviors. Starting with changes to some seed instances, a reasoning engine is designed to fire the pre-defined rule set and act on ontologies to project some semantically associated concepts as target concepts. Certain instances of these target concepts are further selected as target instances, which have a high likelihood of having changed. Our approach is specifically oriented toward the Semantic Web, thus it has intelligence to exploit the semantic associations among data instances and make smart decisions.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPaolo Atzeni, Wesley Chu, Hongjun Lu, Shuigeng Zhou, Tok Wang Ling
PublisherSpringer Verlag
Pages624-638
Number of pages15
ISBN (Print)3540237232, 9783540237235
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3288
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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