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The Scientific World Journal
Volume 2015, Article ID 931258, 9 pages
Research Article

Semantic Clustering of Search Engine Results

1Department of Mathematics & Computer Science, Faculty of Science, Alexandria University, Alexandria 21511, Egypt
2Department of Information Systems & Computers, Faculty of Commerce, Alexandria University, Alexandria 26516, Egypt

Received 13 August 2015; Revised 11 December 2015; Accepted 15 December 2015

Academic Editor: Chun-Wei Tsai

Copyright © 2015 Sara Saad Soliman et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a novel approach for search engine results clustering that relies on the semantics of the retrieved documents rather than the terms in those documents. The proposed approach takes into consideration both lexical and semantics similarities among documents and applies activation spreading technique in order to generate semantically meaningful clusters. This approach allows documents that are semantically similar to be clustered together rather than clustering documents based on similar terms. A prototype is implemented and several experiments are conducted to test the prospered solution. The result of the experiment confirmed that the proposed solution achieves remarkable results in terms of precision.