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Conference object . 2004
License: University of Nottingham Institutional Repository End-User
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Conference object . 2004 . Peer-reviewed
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Nottingham eTheses
Conference object . 2004 . Peer-reviewed
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Article . 2004 . Peer-reviewed
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Article . 2008
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Movie Recommendation Systems Using an Artificial Immune System

Authors: Chen, Qi; Aickelin, Uwe;

Movie Recommendation Systems Using an Artificial Immune System

Abstract

We apply the Artificial Immune System (AIS) technology to the Collaborative Filtering (CF) technology when we build the movie recommendation system. Two different affinity measure algorithms of AIS, Kendall tau and Weighted Kappa, are used to calculate the correlation coefficients for this movie recommendation system. From the testing we think that Weighted Kappa is more suitable than Kendall tau for movie problems.

Country
United Kingdom
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Keywords

FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Average
Top 10%
Average
Green
bronze
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