A novel approach of cluster based optimal ranking of clicked URLs using genetic algorithm for effective personalized web search
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- 作者：Suruchi Chawla sur_chawla@rediffmail.com" class="auth_mail" title="E-mail the corresponding author
- 关键词：Information retrieval ; Search engine ; Information scent ; Clustering ; Genetic algorithm ; Personalized web search
- 刊名：Applied Soft Computing
- 出版年：2016
- 出版时间：September 2016
- 年：2016
- 卷：46
- 期：Complete
- 页码：90-103
- 全文大小：3670 K
文摘
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Genetic Algorithm (GA) is applied for generating the cluster based optimal ranked clicked URLs for effective Personalized Web Search(PWS).
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The computational overhead associated with the use of GA has no impact on the online performance of the PWS using clustered query sessions.
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The experimental results were compared on the basis of percent improvement in average precision of PWS both with and without optimal ranked clicked URLs over Classic IR in the domain Academics, Entertainment and Sports.
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The statistically verified results show more percent improvement in average precision of PWS with optimal ranked clicked URLs than PWS without optimal ranked clicked URLs over Classic IR.