Deep heterogeneous autoencoders for Collaborative Filtering
This paper leverages heterogeneous auxiliary information to address the data sparsity problem of recommender systems. We propose a model that learns a shared feature space from heterogeneous data, such as item descriptions, product tags and online purchase history, to obtain better predictions. Our...
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Main Authors: | , , , , , |
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Other Authors: | |
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2020
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/144026 |
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Institution: | Nanyang Technological University |
Language: | English |