MMALFM: Explainable Recommendation by Leveraging Reviews and Images

12 Nov 2018Zhiyong ChengXiaojun ChangLei ZhuRose C. KanjirathinkalMohan Kankanhalli

Although the latent factor model achieves good accuracy in rating prediction, it suffers from many problems including cold-start, non-transparency, and suboptimal results for individual user-item pairs. In this paper, we exploit textual reviews and item images together with ratings to tackle these limitations... (read more)

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