Hybrid Recommender Systems: The Review of State-of-the-Art Research and Applications
نویسندگان
چکیده
To date, recommender systems are a popular instrument to make personalized suggestions and provide information about items for users. There are many techniques that can be applied for personalization in recommender systems. All these techniques have complementary strengths and weaknesses. A hybrid recommender system combines two or more recommendation techniques to gain better system performance and mitigate the weaknesses of individual ones. Classification of hybrid recommender systems used in this paper is based on the classification proposed by Burke [1]. The need of a systematic review in the area arises from the requirement to summarize all the information about actual methods and algorithms that are used in hybrid recommended system. These materials will be used to support further research activities aiming to develop the auto-switching hybrid recommender system.
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