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COLLABORATIVE WEB RECOMMENDATION SYSTEMS BASED ON AN EFFECTIVE FUZZY ASSOCIATION RULE MINING ALGORITHM (FARM)

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Author(s): A.KUMAR, | Dr. P. THAMBIDURAI

Journal: Indian Journal of Computer Science and Engineering
ISSN 0976-5166

Volume: 1;
Issue: 3;
Start page: 184;
Date: 2010;
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Keywords: Association Rules | Apriori Algorithm | Fuzzy Healthy Association Rule Mining | Collaborative Recommender.

ABSTRACT
With increasing popularity of the web-based systems that are applied in many different areas, they tend to deliver customized informationfor their users by means of utilization of recommendation methods. This recommendation system is mainly classified into two groups:Content-based recommendation and collaborative recommendation system. Content based recommendation tries to recommend web sites similar to those web sites the user has liked, whereas collaborative ecommendation tries to find some users who share similar tastes with the given user and recommends web sites they like to that user. Based on web usage data in adoptive association rule based web mining theassociation rules were applied to personalization. The technique utilize apriori algorithm to generate association rules. Even this method has some disadvantages. To overcome those disadvantages, the author proposed a new algorithm for web recommendation system known as an effective Fuzzy Association Rule Mining Algorithm (FARM). This proposed Fuzzy ARM algorithm for association rule mining in webrecommendation system results in better quality and performance.

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