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Erschienen in:
Social Network Analysis: History, Concepts, and Research Kapitel lesen Erstes Kapitel lesen

2010 | OriginalPaper | Buchkapitel

15. Collaborative Filtering Based on Choosing a Different Number of Neighbors for Each User

verfasst von : Antonio Hernando, Jesús Bobadilla, Francisco Serradilla

Erschienen in: Handbook of Social Network Technologies and Applications

Verlag: Springer US

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Abstract

We present here a new technique for making predictions on recommender systems based on collaborative filtering. The underlying idea is based on selecting a different number of neighbors for each user, instead of, as it is usually made, selecting always a constant number k of neighbors. In this way, we have improved significantly the accuracy of the recommender systems.

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Vorheriges Kapitel Mining Regional Representative Photos from Consumer-Generated Geotagged Photos
Nächstes Kapitel Discovering Communities from Social Networks: Methodologies and Applications
Fußnoten
1
Indeed, \(\sqrt{\mathit{MSD}}\) fulfills the definition of distance given in metric spaces when ∀x ∈ U\(\forall i \in I\ v(x,i)\neq \bullet \).
 
2
In metric spaces, the distance d(x, y) must fulfill that d(x, x) = 0. However, as may be seen, ρ(x, x) = cos(x, x) = 1.
 
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Metadaten
Titel
Collaborative Filtering Based on Choosing a Different Number of Neighbors for Each User
verfasst von
Antonio Hernando
Jesús Bobadilla
Francisco Serradilla
Copyright-Jahr
2010
Verlag
Springer US
Buch
Handbook of Social Network Technologies and Applications

Print ISBN: 978-1-4419-7141-8

Electronic ISBN: 978-1-4419-7142-5

Copyright-Jahr: 2010

DOI
https://doi.org/10.1007/978-1-4419-7142-5_15

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