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International Conference on Database Systems for Advanced Applications

DASFAA 2019: Database Systems for Advanced Applications pp 449–463Cite as

Subspace Ensemble-Based Neighbor User Searching for Neighborhood-Based Collaborative Filtering

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11447))

Abstract

Neighborhood-based collaborative filtering (NCF) typically uses a similarity measure for finding similar users to a target user or similar products on which the target user rated. To find neighbor users, traditional similarity measures rely only on the ratings of co-rated items when calculating similarity of pairwise users. Some hybrid similarity measures can avoid this situation but they suffer from the time-consuming issue. To solve the mentioned issues, the current paper presents an effective method of subspace ensemble-based neighbor user searching (SENUS) for NCF. First, three item subspaces are constructed, or interested, neither interested nor uninterested, and uninterested subspaces. In each subspace, we calculate the co-rating support values for pairwise users. Then, SENUS combines three co-rating support values to get the total co-rating support values for pairwise users, which are utilized to generate direct neighbor users for a target user. For the target user, its neighbor users include direct and indirect ones in SENUS, where its indirect neighbors are the direct neighbors of its direct neighbors. Experimental results on public datasets indicate that the proposed method is promising in recommender systems.

Supported in part by the National Natural Science Foundation of China under Grant No. 61373093, by the Soochow Scholar Project, by the Six Talent Peak Project of Jiangsu Province of China, and by the Collaborative Innovation Center of Novel Software Technology and Industrialization.

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Authors and Affiliations

  1. School of Computer Science and Technology, Joint International Research Laboratory of Machine Learning and Neuromorphic Computing, Soochow University, Suzhou, 215006, Jiangsu, China

    Zepeng Li & Li Zhang

Authors
  1. Zepeng Li
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  2. Li Zhang
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Correspondence to Li Zhang .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Guoliang Li

  2. Duke University, Durham, NC, USA

    Jun Yang

  3. University of Porto, Porto, Portugal

    Joao Gama

  4. Chiang Mai University, Chiang Mai, Thailand

    Juggapong Natwichai

  5. Beihang University, Beijing, China

    Yongxin Tong

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Li, Z., Zhang, L. (2019). Subspace Ensemble-Based Neighbor User Searching for Neighborhood-Based Collaborative Filtering. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11447. Springer, Cham. https://doi.org/10.1007/978-3-030-18579-4_27

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  • DOI: https://doi.org/10.1007/978-3-030-18579-4_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18578-7

  • Online ISBN: 978-3-030-18579-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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