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A Novel Heuristic Web Search Algorithm Based on Gaussian Mutation and Clonal Selection Strategy

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The dynamic nature of information resources and the continuous changes in the information demands of the users has made it very difficult to provide effective methods for web search and document ranking. This paper proposes a novel heuristic web search approach to exploit the relationships among queries and resources based on the search engine's log. The proposed algorithm was verified and extensively tested with numerical examples. The experimental results have shown that our approach significantly outperforms PageRank and HITS (Hyperlink-Induced Topic Search) in most cases.
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Keywords: ARTIFICIAL INTELLIGENT; HYPERLINK-INDUCED TOPIC SEARCH; SEARCH ENGINES; WEB MINING

Document Type: Research Article

Publication date: 2012-03-01

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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