IDENTIFYING USER AND GROUP INFORMATION FROM COLLABORATIVE FILTERING DATASETS
2007 ◽
Vol 21
(02)
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pp. 291-310
Keyword(s):
This paper considers the information that can be captured about users and groups from a collaborative filtering dataset. The aims of the paper are to create a user model and to use this model to explain the performance of a collaborative filtering approach. A number of user and group features are defined and the performance of a collaborative filtering system in producing recommendations for users with different feature values is tested. Graph-based representations of the collaborative filtering space are presented and these are used to define some of the user and group features as well as being used in a recommendation task.
Keyword(s):
2008 ◽
Vol 34
(4)
◽
pp. 2396-2405
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