Evaluating knowledge-based semantic measures on Arabic

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Semantic measures have received a wide attention from researchers to handle various issues in the different tasks of the computational linguistics and information retrieval. In this paper, we experimentally investigate the performances of the knowledge-based semantic measures on the Arabic language. The state-of-the-art semantic measures are adapted to two knowledge sources: a highly structured source (Arabic WordNet) and semi-structured source (Arabic Wikipedia). The performance of the different semantic measures is evaluated on four Arabic benchmark data sets of the word-to-word semantic similarity/relatedness task. The evaluation results show that Wikipedia is a competitive and promising knowledge source in terms of its high degree of coverage and the variety of the extractable semantic features.

Original languageEnglish
Pages (from-to)180-194
Number of pages15
JournalInternational Journal on Communications Antenna and Propagation
Volume4
Issue number5
Publication statusPublished - 1 Oct 2014

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Semantics
Computational linguistics
Information retrieval

Keywords

  • Arabic WordNet
  • Knowledge-Based Methods
  • Semantic Measures
  • Wikipedia

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing
  • Electrical and Electronic Engineering
  • Media Technology

Cite this

Evaluating knowledge-based semantic measures on Arabic. / Saif, Abdulgabbar; Ab Aziz, Mohd Juzaiddin; Omar, Nazlia.

In: International Journal on Communications Antenna and Propagation, Vol. 4, No. 5, 01.10.2014, p. 180-194.

Research output: Contribution to journalArticle

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