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      Representation Learning for Image-based Music Recommendation

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          Abstract

          Image perception is one of the most direct ways to provide contextual information about a user concerning his/her surrounding environment; hence images are a suitable proxy for contextual recommendation. We propose a novel representation learning framework for image-based music recommendation that bridges the heterogeneity gap between music and image data; the proposed method is a key component for various contextual recommendation tasks. Preliminary experiments show that for an image-to-song retrieval task, the proposed method retrieves relevant or conceptually similar songs for input images.

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            Author and article information

            Journal
            28 August 2018
            Article
            1808.09198
            48a16121-9469-457c-ada6-39e19cfdba56

            http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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            Custom metadata
            2 pages, LBRS@RecSys'18
            cs.MM cs.IR cs.SI

            Social & Information networks,Information & Library science,Graphics & Multimedia design

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