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

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 sitessimilar to those web sites the user has liked, whereas collaborative recommendation tries to find some users who share similar tastes with thegiven 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 hassome disadvantages. To overcome those disadvantages, the author proposed a new algorithm for web recommendation system known as aneffective Fuzzy Association Rule Mining Algorithm (FARM). This proposed Fuzzy ARM algorithm for association rule mining in webrecommendation system results in better quality and performance