INFORMATION CHANGE THE WORLD

International Journal of Information Technology and Computer Science(IJITCS)

ISSN: 2074-9007 (Print), ISSN: 2074-9015 (Online)

Published By: MECS Press

IJITCS Vol.5, No.11, Oct. 2013

Utilizing Conceptual Indexing to Enhance the Effectiveness of Vector Space Model

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Author(s)

Aya M. Al-Zoghby, Ahmed Sharaf Eldin Ahmed, Taher T. Hamza

Index Terms

Semantic Web; Semantic Concepts; UWN; Vector Space Model; Arabic Language

Abstract

One of the main purposes of the semantic Web is to improve the retrieval performance of search systems. Unlike keyword based search systems, the semantic search systems aim to discover pages related to the query's concepts rather than merely collecting all pages instantiating its keywords. To that end, the concepts must be defined to be used as a semantic index instead of the traditional lexical one. In fact, The Arabic language is still far from being semantically searchable. Therefore, this paper proposed a model that exploits the Universal Word Net ontology for producing an Arabic Concepts-Space to be used as the index of Semantic Vector Space Model. The Vector Space Model is one of the most common information retrieval models due to its capability of expressing the documents' structure. However, like all keyword-based search systems, its sensitivity to the query's keywords reduces its retrieval effectiveness. The proposed model allows the VSM to represent Arabic documents by their topic, and thus classify them semantically. This, consequently, enhances the retrieval effectiveness of the search system.

Cite This Paper

Aya M. Al-Zoghby, Ahmed Sharaf Eldin Ahmed, Taher T. Hamza,"Utilizing Conceptual Indexing to Enhance the Effectiveness of Vector Space Model", International Journal of Information Technology and Computer Science(IJITCS), vol.5, no.11, pp.1-12, 2013. DOI: 10.5815/ijitcs.2013.11.01

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