2014 | OriginalPaper | Chapter
Boolean Matrix Factorisation for Collaborative Filtering: An FCA-Based Approach
Authors : Dmitry I. Ignatov, Elena Nenova, Natalia Konstantinova, Andrey V. Konstantinov
Published in: Artificial Intelligence: Methodology, Systems, and Applications
Publisher: Springer International Publishing
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We propose a new approach for Collaborative filtering which is based on Boolean Matrix Factorisation (BMF) and Formal Concept Analysis. In a series of experiments on real data (MovieLens dataset) we compare the approach with an SVD-based one in terms of Mean Average Error (MAE). One of the experimental consequences is that it is enough to have a binary-scaled rating data to obtain almost the same quality in terms of MAE by BMF as for the SVD-based algorithm in case of non-scaled data.