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SoURA: a user-reliability-aware social recommendation system based on graph neural network

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Abstract

Exploiting user trust information for developing a recommendation system has gained increasing research interest in recent years. Due to the exchange of opinions about items over the social network, trust plays a crucial role for a user to like or dislike an item. Graph Neural Networks (GNNs), which have the intrinsic power of integrating node information and topological structure, have a high potential to advance the field of trust-aware social recommendation. However, as of now, this area is little explored, with most of the existing GNN-based models ignoring the trust propagation and trust composition properties. To address this issue, in this paper, we propose a novel GNN-based framework that can capture such trust propagation and trust composition aspects by incorporating the concept of ‘user-reliability.’ Our proposed user-reliability-aware social recommendation framework, termed as SoURA, generates the user-embedding and item-embedding with consideration to the user-reliability values, which, in turn, helps in better evaluation of the user trust. Experimental evaluations on the benchmark Ciao and Epinion datasets demonstrate the effectiveness of incorporating user-reliability for finding user-embedding and item embedding in a social recommendation system. The proposed SoURA is found to show a minimum of 25% improvement over the state-of-the-art GNN-based recommendation algorithms.

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Data availability

Data associated with the experiments during studies are publicly available. Also, we have included all the data and source code in the repository https://github.com/Sucheta-d/SoURA-A-User-Reliability-Aware-Social-Recommendation-System-based-on-Graph-Neural-Network, which are available on request.

Notes

  1. https://github.com/Sucheta-d/SoURA-A-User-Reliability-Aware-Social-Recommendation-System-based-on-Graph-Neural-Network.

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Acknowledgements

The authors would like to acknowledge the support from J.C. Bose Fellowship [JBR/2021/000036 to SB] by the SERB, Govt. of India.

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  1. Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India

    Sucheta Dawn, Monidipa Das & Sanghamitra Bandyopadhyay

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  1. Sucheta Dawn
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  2. Monidipa Das
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  3. Sanghamitra Bandyopadhyay
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Correspondence to Sanghamitra Bandyopadhyay.

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Dawn, S., Das, M. & Bandyopadhyay, S. SoURA: a user-reliability-aware social recommendation system based on graph neural network. Neural Comput & Applic 35, 18533–18551 (2023). https://doi.org/10.1007/s00521-023-08679-7

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