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Multiple Auxiliary Information Based Deep Model for Collaborative Filtering

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Abstract

With the ever-growing dynamicity, complexity, and volume of information resources, the recommendation technique is proposed and becomes one of the most effective techniques for solving the so-called problem of information overload. Traditional recommendation algorithms, such as collaborative filtering based on the user or item, only measure the degree of similarity between users or items with single criterion, i.e., ratings. According to the experience of previous studies, single criterion cannot accurately measure the similarity between user preferences or items. In recent years, the application of deep learning techniques has gained significant momentum in recommender systems for better understanding of user preferences, item characteristics, and historical interactions. In this work, we integrate plot information as auxiliary information into the denoising autoencoder (DAE), called SemRe-DCF, which aims at learning semantic representations of item descriptions and succeeds in capturing fine-grained semantic regularities by using vector arithmetic to get better rating prediction. The results manifest that the proposed method can effectively improve the accuracy of prediction and solve the cold start problem.

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Authors and Affiliations

  1. School of Information Science and Technology, Northeast Normal University, Changchun, 130117, China

    Lin Yue, Xiao-Xin Sun, Wen-Zhu Gao, Guo-Zhong Feng & Bang-Zuo Zhang

  2. Key Laboratory of Applied Statistics of Ministry of Education, Northeast Normal University, Changchun, 130024, China

    Lin Yue & Guo-Zhong Feng

  3. School of Environment, Northeast Normal University, Changchun, 130117, China

    Lin Yue

  4. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, 130012, China

    Lin Yue

Authors
  1. Lin Yue
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  2. Xiao-Xin Sun
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  3. Wen-Zhu Gao
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  4. Guo-Zhong Feng
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  5. Bang-Zuo Zhang
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Corresponding authors

Correspondence to Guo-Zhong Feng or Bang-Zuo Zhang.

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Yue, L., Sun, XX., Gao, WZ. et al. Multiple Auxiliary Information Based Deep Model for Collaborative Filtering. J. Comput. Sci. Technol. 33, 668–681 (2018). https://doi.org/10.1007/s11390-018-1848-x

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  • DOI: https://doi.org/10.1007/s11390-018-1848-x

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