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Implementation of SVM+PSO Model in Monolingual and Cross Lingual Information Retrieval Ranking

Journal: International Journal of Advanced Trends in Computer Science and Engineering (IJATCSE) (Vol.10, No. 4)

Publication Date:

Authors : ;

Page : 2727-2733

Keywords : Information Retrieval; Machine Learning; PSO; SVM; Word2Vec.;

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Now a day's many research works are going on in the field of Information Retrieval Ranking. Retrieval and Ranking of information from the huge database of internet world is become a most useful and interesting task. Machine learning plays the major role now days. In this paper we have worked for monolingual and cross lingual information retrieval ranking in which the retrieval of document within the same language and retrieval of document in different language has been done. We take English language for monolingual IR ranking and for cross lingual we take Hindi queries and get documents in English. TREC 2008 QA Dataset and FIRE 2011 ADHOC Dataset has been taken in this work respectively. Finally the performance Evaluation has been done for SVM, PSO and SVM+PSO and the results has been compared. The results clearly explain that SVM+PSO model gives best result in compare to other two.

Last modified: 2021-08-10 17:32:18