SCIENCE CHINA Information Sciences, Volume 61, Issue 12: 122102(2018) https://doi.org/10.1007/s11432-017-9343-5

LionRank: lion algorithm-based metasearch engines for re-ranking of webpages

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  • ReceivedOct 18, 2017
  • AcceptedMay 22, 2018
  • PublishedNov 20, 2018


Due to the rapid growth of the web, the process ofcollecting the relevant web pages based on the user query is one of themajor challenging tasks in recent days. Hence, it is very complicated forthe users to know the most relevant information even though various searchengines are widely employed. To deal with users' trouble in identifying therelevant information from the web, we have proposed a meta-lion searchengine to capture and analyze the ranking scores of various search enginesand thereby, generate the re-ranked score results. Accordingly, LionRank, alion algorithm-based meta-search engine is proposed for the re-ranking ofthe web pages. Here, different features like text based, factor based, rankbased and classifier based features are used by the underlying searchengines. In classifier based feature extraction, we have used the fuzzy integrated extended nearest neighbor (FENN) classifier to include thesemantics in feature extraction. Moreover, an intelligent re-ranking processis proposed based on the lion algorithm to fuse the features scoresoptimally. Finally, the results of the proposed LionRank is analyzed withthe web page database collected through four benchmark queries, and thequantitative performance are analyzed using precision, recall, and F-score.From the results, we proved that the proposed LionRank obtained the maximumF-score of 81%as compared with that of existing search engines likeQuadRank, Outrank, Google, Yahoo, and Bing.


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