Probabilistic Approaches to Recommendations

Ebook Details

Authors

Nicola Barbieri, Giuseppe Manco, Ettore Ritacco

Year 2014
Pages 198
Publisher Morgan &amp
Language en
ISBN 9781627052573
File Size 13.06 MB
File Format PDF
Download Counter 207
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Ebook Description

The importance of accurate recommender systems has been widely recognized by academia and industry, and recommendation is rapidly becoming one of the most successful applications of data mining and machine learning. Understanding and predicting the choices and preferences of users is a challenging task: real-world scenarios involve users behaving in complex situations, where prior beliefs, specific tendencies, and reciprocal influences jointly contribute to determining the preferences of users toward huge amounts of information, services, and products. Probabilistic modeling represents a robust formal mathematical framework to model these assumptions and study their effects in the recommendation process.