Titlebook: Recommender Systems; The Textbook Charu C. Aggarwal Textbook 2016 Springer Nature Switzerland AG 2016 Collaborative filtering.Data mining.R

Antecedent

Social and Trust-Centric Recommender Systems,hough some of these methods are discussed in Chapter ., the focus of this chapter is primarily on recommending nodes and links in network settings. Social context is a much broader concept, not only including social (network) links, but also various types of side information, such as tags or folkson

細菌等

Attack-Resistant Recommender Systems,com and Epinions.com. Like any other data-mining system, the effectiveness of a recommender system depends almost exclusively on the quality of the data available to it. Unfortunately, there are significant motivations for participants to submit incorrect feedback about items for personal gain or fo

FANG

生氣地

An Introduction to Recommender Systems, click of a mouse. A typical methodology to provide feedback is in the form of ., in which users select numerical values from a specific evaluation system (e.g., five-star rating system) that specify their likes and dislikes of various items.

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BROW

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類似思想

Evaluating Recommender Systems,The evaluation of collaborative filtering shares a number of similarities with that of classification. This similarity is due to the fact that collaborative filtering can be viewed as a generalization of the classification and regression modeling problem (cf. section?. of Chapter?.).

infarct

Time- and Location-Sensitive Recommender Systems,In many real scenarios, the buying and rating behaviors of customers are associated with temporal information. For example, the ratings in the Netflix Prize data set are associated with a “.” variable, and it was eventually shown?[310] how the temporal component could be used to improve the rating predictions.

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Charu C. AggarwalIncludes exercises and assignments, with instructor access to a solutions manual.Illustrations throughout aid in comprehension.Provides many examples to simplify exposition and facilitate in learning.