A comparison of corpusbased and structural methods on approximation of semantic relatedness in ontologies

Tuukka Ruotsalo*, Eetu Mäkelä

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

5 Citations (Scopus)

Abstract

In this paper, the authors compare the performance of corpus-based and structural approaches to determine semantic relatedness in ontologies. A large light-weight ontology and a news corpus are used as materials. The results show that structural measures proposed by Wu and Palmer, and Leacock and Chodorow have superior performance when cut-off values are used. The corpus-based method Latent Semantic Analysis is found more accurate on specific rank levels. In further investigation, the approximation of structural measures and Latent Semantic Analysis show a low level of overlap and the methods are found to approximate different types of relations. The results suggest that a combination of corpus-based methods and structural methods should be used and appropriate cut-off values should be selected according to the intended use case.

Original languageEnglish
Pages (from-to)39-56
Number of pages18
JournalINTERNATIONAL JOURNAL ON SEMANTIC WEB AND INFORMATION SYSTEMS
Volume5
Issue number4
DOIs
Publication statusPublished - Oct 2009
MoE publication typeA1 Journal article-refereed

Keywords

  • Latent Semantic Analysis
  • Ontologies
  • Semantic Relatedness
  • Semantic Web
  • Structural Measures

Fingerprint

Dive into the research topics of 'A comparison of corpusbased and structural methods on approximation of semantic relatedness in ontologies'. Together they form a unique fingerprint.

Cite this