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Reseach Article

Description and Evaluation of Semantic Similarity Measures Approaches

by Thabet Slimani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 80 - Number 10
Year of Publication: 2013
Authors: Thabet Slimani
10.5120/13897-1851

Thabet Slimani . Description and Evaluation of Semantic Similarity Measures Approaches. International Journal of Computer Applications. 80, 10 ( October 2013), 25-33. DOI=10.5120/13897-1851

@article{ 10.5120/13897-1851,
author = { Thabet Slimani },
title = { Description and Evaluation of Semantic Similarity Measures Approaches },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 80 },
number = { 10 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 25-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume80/number10/13897-1851/ },
doi = { 10.5120/13897-1851 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:54:11.669030+05:30
%A Thabet Slimani
%T Description and Evaluation of Semantic Similarity Measures Approaches
%J International Journal of Computer Applications
%@ 0975-8887
%V 80
%N 10
%P 25-33
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In recent years, semantic similarity measure has a great interest in Semantic Web and Natural Language Processing (NLP). Several similarity measures have been developed, being given the existence of a structured knowledge representation offered by ontologies and corpus which enable semantic interpretation of terms. Semantic similarity measures compute the similarity between concepts/terms included in knowledge sources in order to perform estimations. This paper discusses the existing semantic similarity methods based on structure, information content and feature approaches. Additionally, we present a critical evaluation of several categories of semantic similarity approaches based on two standard benchmarks. The aim of this paper is to give an efficient evaluation of all these measures which help researcher and practitioners to select the measure that best fit for their requirements.

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Index Terms

Computer Science
Information Sciences

Keywords

Similarity Measure structure-based measures edge-counting feature-based measures hybrid measures Wornet MeSH ontology