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Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering

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Foundations of Intelligent Systems (ISMIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12117))

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Abstract

In this work, we study the utility of graph embeddings to generate latent user representations for trust-based collaborative filtering. In a cold-start setting, on three publicly available datasets, we evaluate approaches from four method families: (i) factorization-based, (ii) random walk-based, (iii) deep learning-based, and (iv) the Large-scale Information Network Embedding (LINE) approach. We find that across the four families, random-walk-based approaches consistently achieve the best accuracy. Besides, they result in highly novel and diverse recommendations. Furthermore, our results show that the use of graph embeddings in trust-based collaborative filtering significantly improves user coverage.

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Notes

  1. 1.

    Implementation used: https://github.com/palash1992/GEM-Benchmark.

  2. 2.

    Implementation used: https://github.com/benedekrozemberczki/role2vec.

  3. 3.

    Implementation used: https://github.com/phanein/deepwalk.

  4. 4.

    Implementation used https://github.com/aditya-grover/node2vec.

  5. 5.

    Implementation used: https://github.com/benedekrozemberczki/role2vec.

  6. 6.

    Implementation used: https://github.com/ShelsonCao/DNGR.

  7. 7.

    Implementation used: https://github.com/suanrong/SDNE.

  8. 8.

    Implementation used: https://github.com/williamleif/GraphSAGE.

  9. 9.

    Implementation used: https://github.com/tangjianpku/LINE.

  10. 10.

    Details on the hyperparameter optimization can be found at: https://github.com/tduricic/trust-recommender/blob/master/docs/hyperparameter-optimization.md.

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Author information

Authors and Affiliations

  1. Graz University of Technology, Graz, Austria

    Tomislav Duricic, Denis Helic & Elisabeth Lex

  2. Know-Center GmbH, Graz, Austria

    Tomislav Duricic, Hussain Hussain, Emanuel Lacic & Dominik Kowald

Authors
  1. Tomislav Duricic
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  2. Hussain Hussain
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  3. Emanuel Lacic
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  4. Dominik Kowald
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  5. Denis Helic
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  6. Elisabeth Lex
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Corresponding author

Correspondence to Tomislav Duricic .

Editor information

Editors and Affiliations

  1. Graz University of Technology, Graz, Austria

    Denis Helic

  2. University of Klagenfurt, Klagenfurt, Austria

    Gerhard Leitner

  3. Graz University of Technology, Graz, Austria

    Martin Stettinger

  4. Graz University of Technology, Graz, Austria

    Alexander Felfernig

  5. University of North Carolina at Charlotte, Charlotte, NC, USA

    Zbigniew W. Raś

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Duricic, T., Hussain, H., Lacic, E., Kowald, D., Helic, D., Lex, E. (2020). Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering. In: Helic, D., Leitner, G., Stettinger, M., Felfernig, A., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2020. Lecture Notes in Computer Science(), vol 12117. Springer, Cham. https://doi.org/10.1007/978-3-030-59491-6_17

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  • DOI: https://doi.org/10.1007/978-3-030-59491-6_17

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