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A Novel Multidimensional Comments and Co-preference Aware Recommendation Algorithm

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2020)

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Abstract

A recommendation system creates a personalized experience for each customer, which helps companies boost the average order value and the amount of revenue generated from each customer. In a typical recommendation system, comments typify the group wisdom of users, which can reflect their feelings toward the product in multiple dimensions. Co-preference mirrors common preference of a group of users. By mining the multidimensional comments and co-preference relationship comprehensively, it is justifiable to recommend products that both have a good reputation and conform to users’ interests. However, the existing related methods have two problems. Firstly, there is lack of further consideration on how to fully utilize comments of products from multiple dimensions for recommendation. Secondly, how to mine co-preference relationship and combine it with multidimensional comments for recommendation is seldom considered. Therefore, a novel recommendation algorithm is proposed, which mines the comments from multiple dimensions and then converges it with co-preference relationship for recommendation. Experiments conducted on two real-world datasets reveal that our proposed method improves the accuracy in terms of MAE and RMSE, compared with state-of-the-art algorithms.

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Authors and Affiliations

  1. Central University of Finance and Economics, Beijing, 100081, China

    Yanmei Zhang, Nana Song, Xiaoyi Tang & Huaihu Cao

Authors
  1. Yanmei Zhang
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  2. Nana Song
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  3. Xiaoyi Tang
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  4. Huaihu Cao
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Corresponding author

Correspondence to Yanmei Zhang .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. Xi’an Jiaotong-Liverpool University, Suzhou, China

    Xinheng Wang

  3. London South Bank University, London, UK

    Muddesar Iqbal

  4. Hangzhou Dianzi University, Hangzhou, China

    Yuyu Yin

  5. Zhejiang University, Hangzhou, China

    Jianwei Yin

  6. Fudan University, Shanghai, China

    Ning Gu

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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhang, Y., Song, N., Tang, X., Cao, H. (2021). A Novel Multidimensional Comments and Co-preference Aware Recommendation Algorithm. In: Gao, H., Wang, X., Iqbal, M., Yin, Y., Yin, J., Gu, N. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 349. Springer, Cham. https://doi.org/10.1007/978-3-030-67537-0_32

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  • DOI: https://doi.org/10.1007/978-3-030-67537-0_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67536-3

  • Online ISBN: 978-3-030-67537-0

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