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A Survey of Methods of Collaborative Filtering Techniques

机译:协同滤波技术方法调查

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Collaborative Filtering technique is a recognized technique used in recommender systems for providing useful recommendations to users. The domain dependent nature of Collaborative Filtering allows more diverse set of recommendations at the same time making the user interested in recommendation process. Cold start problem is the most inevitable problem in collaborative filtering which makes it difficult for systems to make suitable recommendations. There are various algorithms available for Collaborative filtering technique that try and alleviate cold start problem. This study deals with the Collaborative filtering approaches and analyses that how different algorithms are applied to real life problems. It also discusses the merits and drawbacks of each approach. This review concludes that hybrid approach performs better than the other collaborative filtering algorithms.
机译:协作过滤技术是用于推荐系统中的公认技术,用于向用户提供有用的建议。协同过滤的域依赖性本质允许更多样化的建议,同时使用户对推荐过程感兴趣。冷启动问题是协同过滤中最不可避免的问题,这使得系统难以制定合适的建议。有各种可用于协同过滤技术的算法,试图缓解冷启动问题。本研究涉及协作过滤方法,并分析了不同的算法如何应用于现实生活问题。它还讨论了每种方法的优点和缺点。此述评得出结论,混合方法比其他协作滤波算法更好。

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