Titlebook: Recommender Systems Handbook; Francesco Ricci,Lior Rokach,Bracha Shapira Book 2022Latest edition Springer Science+Business Media, LLC, par

Barter

Advances in Collaborative Filtering. The CF methods discussed in this chapter have been proposed a decade ago but still show state-of-the art accuracy in recent studies. The modeling patterns identified in this chapter are applicable to a variety of recommender problems such as item recommendation, rating prediction, cold start recommendation and context-aware recommenders.

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烦人

Defiance

Advances in Collaborative FilteringF algorithms have shown great prediction quality both in academic research and in industrial applications. This chapter surveys core methods in the field. Matrix factorization techniques, which became a first choice for implementing CF, are described together with other innovations. We also describe

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爱管闲事

Context-Aware Recommender Systems: From Foundations to Recent Developmentson, information retrieval, ubiquitous and mobile computing, data mining, marketing, and management. Prior work has extensively demonstrated that relevant contextual information does matter in recommender systems and that it is important to take this information into account when providing recommenda