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Adapting Ratings in Memory-Based Collaborative Filtering using Linear Regression

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2 Author(s)
Kunegis, J. ; Tech. Univ. Berlin, Berlin ; Albayrak, S.

We show that the standard memory-based collaborative filtering rating prediction algorithm using the Pearson correlation can be improved by adapting user ratings using linear regression. We compare several variants of the memory-based prediction algorithm with and without adapting the ratings. We show that in two well-known publicly available rating datasets, the mean absolute error and the root mean squared error are reduced by as much as 20% in all variants of the algorithm tested.

Published in:

Information Reuse and Integration, 2007. IRI 2007. IEEE International Conference on

Date of Conference:

13-15 Aug. 2007