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Erschienen in:
Recommender Systems: Introduction and Challenges Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

3. Advances in Collaborative Filtering

verfasst von : Yehuda Koren, Robert Bell

Erschienen in: Recommender Systems Handbook

Verlag: Springer US

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Abstract

The collaborative filtering (CF) approach to recommenders has recently enjoyed much interest and progress. The fact that it played a central role within the recently completed Netflix competition has contributed to its popularity. This chapter surveys the recent progress in the field. Matrix factorization techniques, which became a first choice for implementing CF, are described together with recent innovations. We also describe several extensions that bring competitive accuracy into neighborhood methods, which used to dominate the field. The chapter demonstrates how to utilize temporal models and implicit feedback to extend models accuracy. In passing, we include detailed descriptions of some the central methods developed for tackling the challenge of the Netflix Prize competition.

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Vorheriges Kapitel A Comprehensive Survey of Neighborhood-Based Recommendation Methods
Nächstes Kapitel Semantics-Aware Content-Based Recommender Systems
Fußnoten
1
Recall that the dot product between two vectors \(x,y \in \mathbb{R}^{f}\) is defined as: \(x^{T}y =\sum _{ k=1}^{f}x_{k} \cdot y_{k}\).
 
2
Notational clarification: With other neighborhood models it was beneficial to use S k (i; u), which denotes the k items most similar to i among those rated by u. Hence, if u rated at least k items, we will always have | S k (i; u) | = k, regardless of how similar those items are to i. However, | R k (i; u) | is typically smaller than k, as some of those items most similar to i were not rated by u.
 
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2.
Bell, R., and Koren, Y., “Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights”, IEEE International Conference on Data Mining (ICDM’07), pp. 43–52, 2007.
3.
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Metadaten
Titel
Advances in Collaborative Filtering
verfasst von
Yehuda Koren
Robert Bell
Copyright-Jahr
2015
Verlag
Springer US
Buch
Recommender Systems Handbook

Print ISBN: 978-1-4899-7636-9

Electronic ISBN: 978-1-4899-7637-6

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-1-4899-7637-6_3

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