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I Know Why You Like This Movie: Interpretable Efficient Multimodal Recommender

Barbara Rychalska, Dominika Basaj, Jacek Dąbrowski, Michał Daniluk . Arxiv 2020 – 0 citations

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Datasets Hashing Methods Recommender Systems

Recently, the Efficient Manifold Density Estimator (EMDE) model has been introduced. The model exploits Local Sensitive Hashing and Count-Min Sketch algorithms, combining them with a neural network to achieve state-of-the-art results on multiple recommender datasets. However, this model ingests a compressed joint representation of all input items for each user/session, so calculating attributions for separate items via gradient-based methods seems not applicable. We prove that interpreting this model in a white-box setting is possible thanks to the properties of EMDE item retrieval method. By exploiting multimodal flexibility of this model, we obtain meaningful results showing the influence of multiple modalities: text, categorical features, and images, on movie recommendation output.

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