Statistical Methods for Recommender Systems - Tapa dura

Chen, Bee-Chung; Agarwal, Deepak K.

 
9781107036079: Statistical Methods for Recommender Systems
Tapa dura
ISBN 10: 1107036070 ISBN 13: 9781107036079
Editorial: Cambridge University Press, 2016

Sinopsis

Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.

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Acerca de los autores

Dr Deepak Agarwal is a big data analyst with more than fifteen years of experience developing and deploying state-of-the-art machine learning and statistical methods for improving the relevance of web applications. He is also experienced in conducting new scientific research to solve notoriously difficult big data problems, especially in the areas of recommender systems and computational advertising. He is a Fellow of the American Statistical Association and associate editor of two top-tier journals in statistics.

Dr Bee-Chung Chen is a Senior Staff Engineer and Applied Researcher at LinkedIn. He has been a key designer of the recommendation algorithms that power LinkedIn homepage and mobile feeds, Yahoo! homepage, Yahoo! News and other sites. Dr Chen is a leading technologist with extensive industrial and research experience. His research areas include recommender systems, machine learning and big data analytics.

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Editorial
Cambridge University Press
Año de publicación
2016
Idioma
Inglés
ISBN 10 
1107036070
ISBN 13 
9781107036079
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
298
Contacto del fabricante
no disponible
Persona responsable
gpsr@libri.de
gpsr@libri.de

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