Online Comment Analysis for Recommendation

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

Online Comment Analysis for Recommendation
Author(s):
Tushar Mehmi
Keywords:
Automated Collaborative Filtering (ACF),collaborative filtering (CF)
Abstract
This Research paper analysis the use of soft computing techniques to develop recommendation systems. Information on the Internet grows rapidly and users should be directed to high quality Websites those are relevant to their personal interests. However, there is no way to Judge these web pages. Displaying quality content to users based on ratings or past Search results are not adequate. There’s a lacking of powerful automated process combining human opinions with machine learning of personal preference. The ongoing rapid expansion of the Internet greatly increases the necessity of eﬀective recommender systems for ﬁltering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, uniﬁcation and comparison of diﬀerent approaches are lacking, which impedes further advances.
Article Details
Unique Paper ID: 143109 Publication Volume & Issue: Volume 2, Issue 7 Page(s): 636 - 640
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