Abstract

The Recommender systems have now become an important part of web based systems. They aim to automatically products/services to customers; there are still three challenges in e-services: (1) items or user profiles often present complicated tree structures (2) online users’ preferences are often indefinite (3)same product getting recommended repeatedly leaving other equal quality products under starvation. This studyproposes a method for modeling fuzzy tree-structured user preferences, in which fuzzy set techniques are used to express user preferences. We are using comprehensive tree matching method which can match two tree-structured data and identify their corresponding parts by considering all the information about tree structures, node attributes and weights. The proposed fuzzy tree-structured user preference profile reflects user preferences effectively, and the recommendation approach demonstrates excellent performance for tree-structured items. The other main idea of this study is that we have included group recommendation through which we can recommend a product to a group of people.

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