LightFIG: simplifying and powering feature interactions via graph for recommendation
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DOI: 10.7717/peerj-cs.1019
Abstract: The attributes of users and items contain key information for recommendation. The latest advances demonstrate that better representations can be learned by performing graph convolutions on attribute graph of the user-item pair. Recently proposed models… read more here.
Keywords: recommendation; user item; item attributes; item ... See more keywords