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: 2021-08-10
Authors : Shweta Pandey Iti Mathur Nisheeth Joshi;
Page : 2727-2733
Keywords : Information Retrieval; Machine Learning; PSO; SVM; Word2Vec.;
Abstract
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.
Other Latest Articles
- Does the Education Games with adding some Entertainment Game Elements will attract the children?
- Fake News Detection using Machine Learning Algorithm
- Development of Novel Predictive Models For Estimation of Nitrogen Fixation Under Cultural and Field Conditions Using R Software
- Density based Traffic Control with Alert System using Arduino and NodeMCU
- Barangay Profiling System with Analytics
Last modified: 2021-08-10 17:32:18