A Survey of Various Hybrid based Recommendation Method
نویسندگان
چکیده
Recommender systems play an important role in filtering and customizing the desired information. Recommender system are divided into 3 categories i.e collaborative filtering , content-based filtering, and hybrid filtering and they are the most adopted techniques being utilized in recommender systems. In this paper describes about various limitations of current recommendation methods such as cold-start problem ,Gray-sheep problem and discuss possible extensions that can improve recommendation capabilities in range of applications extensions such as, improvement of understanding of users and items incorporation of the contextual information into the recommendation process, support for multi-criteria ratings. The paper consist the survey of various hybrid filtering to overcome the drawbacks and extensions of a forementioned techniques .
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