Abstract

A Recommender System (RS) is a composition of software tools and machine learning techniques that provides valuable piece of advice for items or services chosen by a user. Recommender systems are currently useful in both the research and in the commercial areas. Numerous approaches have been proposed for providing recommendations. Certainly, recommendation systems have an assortment of properties that may entail experiences of user such as user preference, prediction accuracy, confidence, trust, etc. In this paper we present a categorical reassess of the field of recommender systems and Approaches for Evaluation of Recommendation System to propose the recommendation method that would further help to enhance opinion mining through recommendations.

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