Deep heterogeneous autoencoders for Collaborative Filtering

• المؤلفون الرئيسيون: Li, Tianyu, Ma, Yukun, Xu, Jiu, Stenger, Björn, Liu, Chen, Hirate, Yu
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: Conference or Workshop Item
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Computer science and engineering; Deep Autoencoder; Heterogeneous Data
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/144026

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...