News Recommendation Systems Using Web Mining: A Study
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2014 by IJETT Journal|
|Year of Publication : 2014|
|Authors : Dr. M. Durairaj , K. Muthu Kumar
Dr. M. Durairaj , K. Muthu Kumar. "News Recommendation Systems Using Web Mining: A Study", International Journal of Engineering Trends and Technology (IJETT), V12(6),293-299 June 2014. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
News reading has changed with the advance of the World Wide Web (www), from the traditional model of news consumption via physical newspaper subscription to access to thousands of sources via the internet. Online news reading has become very popular as the web provides access to news articles from millions of sources around the world web users are undergoing a transformation and they are now expressing themselves in the form of sharing their opinions on an item through ratings and reviews or comments, through sharing and tagging content, or by contributing new content. Recommendation, filtering, and summary of Web news has received much attention in Web intelligence, aiming to find interesting news and summarize concise content for users. In this paper, we surveyed different proposals and approaches that take users’ collective intelligence through their interactions with the contents, their contribution and navigation patterns, and finally suggests best recommendations. This paper also compares the various models used to create a solution for the problems of news recommendation.
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Web mining, Lexical Chains, Bayesian Framework for User Interest Prediction, Topic Analysis Model, Keyword Extraction Algorithm, Newsletters System and collective intelligence..