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An Introduction to Recommender Systems Read chapter Read first chapter

2016 | OriginalPaper | Chapter

8. Context-Sensitive Recommender Systems

Author : Charu C. Aggarwal

Published in: Recommender Systems

Publisher: Springer International Publishing

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Abstract

“For me context is the key – from that comes the understanding

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previous chapter Evaluating Recommender Systems
next chapter Time- and Location-Sensitive Recommender Systems
Footnotes
1
In the traditional database context, the notions of dimension and attribute mean the same thing. In this case, however, they do not mean the same thing. A set of attributes is associated with a dimension.
 
2
This similarity might not be obvious at first because the two equations do not use the same notation. Each k-dimensional factor vector \(\overline{v_{i}}\) of the factorization machine is equivalent to one of the k-dimensional rows of either the user, item, or context factor matrix in Equation 8.6.
 
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Metadata
Title
Context-Sensitive Recommender Systems
Author
Charu C. Aggarwal
Copyright Year
2016
Book
Recommender Systems

Print ISBN: 978-3-319-29657-9

Electronic ISBN: 978-3-319-29659-3

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-29659-3_8

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