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Recommender System Based on User Ratings: a Comprehensive Study and Future Challenges
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Abstract
With immense growth of information on web, the order of making choices about a particular item or product or to advice somebody on a particular product has become difficult. There is an overwhelming amount of information available on web. This has indeed lead to a clear demand for an automated tool or a method which will assist users in finding right information at the right place and at right time. The automated system is the Recommender System which provides tools to help user locate and retrieve information according to their interests. With exponential growth of information and choices available on web, users find it difficult to make right decision about items or products. Recommender system assists user in decision making process. In this paper we present a comprehensive study on very important tool i.e. recommender system which is the need of the day. The study includes the brief introduction to the different recommender systems available in the ecommerce, recommender system based on single rating, multi criteria rating(representing a two dimensional matrix of user and item) and an extension, multi dimensional(extending two dimensional matrix of user and item to ‘n’ dimensional matrix of user, time, content, space, emotions, color etc). We also present the future challenges that lie in the area of recommender system.
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