title: Semantic Clustering of Search Engine Results.
abstract: 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.
authors.affiliation: Department of Mathematics & Computer Science, Faculty of Science, Alexandria University, Alexandria 21511, Egypt.
authors.forename: Sara Saad
authors.initials: SS
authors.lastname: Soliman
authors.affiliation: Department of Information Systems & Computers, Faculty of Commerce, Alexandria University, Alexandria 26516, Egypt.
authors.forename: Maged F
authors.initials: MF
authors.lastname: El-Sayed
authors.affiliation: Department of Mathematics & Computer Science, Faculty of Science, Alexandria University, Alexandria 21511, Egypt.
authors.forename: Yasser F
authors.initials: YF
authors.lastname: Hassan