Due to the ever-increasing amount of various information provided by internet, recommendation systems are now used in a large number fields as efficient tools get rid overload. The content-based, collaborative-based and hybrid methods three classical techniques, whereas not all real-world problems (e.g. food problem) can be best addressed such techniques. This paper is devoted solving problem b...

due to the quick growth of the world wide web, retrieval of useful informationfrom the internet for a particular web user or a group of users becomes verydifficult. recommendation systems using web usage mining help providing anadaptive web environment for the web users. this paper presents a novel approachfor page recommendation using fuzzy association rule mining algorithm. thismethod extract...

Detecting communities plays a vital role in studying group level patterns of a social network and it can be helpful in developing several recommendation systems such as movie recommendation, book recommendation, friend recommendation and so on. Most of the community detection algorithms can detect disjoint communities only, but in the real time scenario, a node can be a member of more than one ...

recommender systems (rs) provide personalized recommendation according to user need by analyzing behavior of users and gathering their information. one of the algorithms used in recommender systems is user-based collaborative filtering (cf) method. the idea is that if users have similar preferences in the past, they will probably have similar preferences in the future. the important part of col...