Review Paper on Efficient Approach for Context Aware Recommendation System
Keywords:
Context-Aware Recommender Systems(CARs); Cold-Start Problem; Hybrid SystemAbstract
Context-Aware Recommender Systems (CARSs) have to face the cold-start problem, that is, there is no possibility to provide proper recommendations for the new users, items or contextual situations. In this paper, the methods proposed for solving cold start problem by exploiting various hybridization techniques, in order to take advantage of the strengths of different CARS algorithms while removing their weaknesses in a given (cold start) situation. The initial analysis has shown that basic CARS algorithms are used and hybridized to achieve an overall optimal performance. Here, combined multiple pre-filters (Combining Multiple approaches) are used with Hybridization to solve the cold-start problem. It is used to generate accurate ratings and better performance of CARS.
References
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