Semantic Clustering of Search Engine Results

Autor: Sara Saad Soliman, Maged F. El-Sayed, Yasser F. Hassan
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: The Scientific World Journal, Vol 2015 (2015)
Druh dokumentu: article
ISSN: 2356-6140
1537-744X
DOI: 10.1155/2015/931258
Popis: 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.
Databáze: Directory of Open Access Journals
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