Taher T. Hamza

Work place: Computer Science Department, Faculty of Computers & Information Science, Mansoura University, Egypt

E-mail: taher_hamza@yahoo.com

Website:

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Biography

Taher T. Hamza: Assis. Professor of Computer Sciences, Faculty of Computers and Information-Mansoura University, Vice Dean For Graduate Studies and Research.

Author Articles
Utilizing Conceptual Indexing to Enhance the Effectiveness of Vector Space Model

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

DOI: https://doi.org/10.5815/ijitcs.2013.11.01, Pub. Date: 8 Oct. 2013

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.

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