DocumentCode :
2313192
Title :
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
Link To Document :
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