News Recommendation Using Term Frequency and Document Similarity - Couverture souple

Gupta, Ashwini; Jain, Vaibhav

 
9783659949760: News Recommendation Using Term Frequency and Document Similarity
Couverture souple
ISBN 10 : 3659949760 ISBN 13 : 9783659949760
Editeur : LAP LAMBERT Academic Publishing, 2016

Synopsis

Excessive overloading of information has become a serious problem recently. Extensive use of technology has made life easier but it also lead to access of information creation. There are several news portals where lots of information gets uploaded daily. As it is an era of E-News where online news reading has become a common habit of people. People are more likely to read News on Web rather than on Newspaper or other media. It becomes harder for user to find relevant and popular news in small time. Now a day it has become a key challenge as everyone has different liking and reading habits. A solution to this problem is news recommendation system. A Content Based Recommendation is developed which recommends news on the basis of article similarity with query and document similarity. Measures like term frequency count & document similarity are used to find out the similarity of query in the complete corpus of News articles. Each document is compared with every document available in corpus and content matching is performed to find out the similarity score. Results are evaluated on two different datasets using measures are used to evaluate the relevancy of recommended News articles.

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Présentation de l'éditeur

Excessive overloading of information has become a serious problem recently. Extensive use of technology has made life easier but it also lead to access of information creation. There are several news portals where lots of information gets uploaded daily. As it is an era of E-News where online news reading has become a common habit of people. People are more likely to read News on Web rather than on Newspaper or other media. It becomes harder for user to find relevant and popular news in small time. Now a day it has become a key challenge as everyone has different liking and reading habits. A solution to this problem is news recommendation system. A Content Based Recommendation is developed which recommends news on the basis of article similarity with query and document similarity. Measures like term frequency count & document similarity are used to find out the similarity of query in the complete corpus of News articles. Each document is compared with every document available in corpus and content matching is performed to find out the similarity score. Results are evaluated on two different datasets using measures are used to evaluate the relevancy of recommended News articles.

Biographie de l'auteur

Ms Ashwini Gupta completed Masters in engineering from IET DAVV Indore in 2016. Dr. Vaibhav Jain is Asst. Professor at Inst. of Engg. & Technology Devi Ahilya Vishwavidyalaya Indore, India. He has obtained his PhD degree in Computer Science from Indian Institute of Technology Delhi in 2015. His current research area includes information retrieval.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2016
Langue
anglais
ISBN 10 
3659949760
ISBN 13 
9783659949760
Reliure
Broché
Nombre de pages
52
Coordonnées du fabricant
non disponible
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