An FCA-based Boolean Matrix Factorisation for Collaborative Filtering

2013-10-16 · Elena Nenova, Dmitry I. Ignatov, Andrey V. Konstantinov

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 the SVD- and NMF-based algorithms 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 than for the SVD-based algorithm in case of non-scaled data.

📄 PDF Abstract BibTeX arXiv:1310.4366

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