A Survey of Semantic Similarity Methods for Ontology Based Information Retrieval

Author

Saruladha, K. ; Aghila, G. ; Raj, Sajina

Author_Institution

Dept. of Comput. Sci. & Eng., Pondciherry Eng. Coll., Pondicherry, India

fYear

2010

fDate

9-11 Feb. 2010

Firstpage

297

Lastpage

301

Abstract

This paper discusses the various approaches used for identifying semantically similar concepts in an ontology. The purpose of this survey is to explore how these similarity computation methods could assist in ontology based query expansion. This query expansion method based on the similarity function is expected to improve the retrieval effectiveness of the ontology based Information retrieval models. Various similarity computation methods fall under three categories: Edge counting, information content and node based counting. The limitations of each of these approaches have been discussed in this paper.

Keywords

information retrieval; ontologies (artificial intelligence); edge counting; information content; node based counting; ontology based information retrieval; query expansion method; semantic similarity methods; Computer science; Educational institutions; Humans; Information retrieval; Instruction sets; Length measurement; Machine learning; Ontologies; Taxonomy; Weight measurement; Ontology; concept ual similarity; corpus based; information retrieval; similarity method; taxonomy;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Computing (ICMLC), 2010 Second International Conference on

Conference_Location

Bangalore

Print_ISBN

978-1-4244-6006-9

Electronic_ISBN

978-1-4244-6007-6

Type

conf

DOI

10.1109/ICMLC.2010.63

Filename

5460722