A First Principles Approach to Trust-Based Recommendation Systems

• URL: http://arxiv.org/abs/2407.00062v1
• Date: Mon, 17 Jun 2024 05:23:00 GMT
• Title: A First Principles Approach to Trust-Based Recommendation Systems
• Authors: Paras Stefanopoulos, Ahad N. Zehmakan, Sourin Chatterjee,
• Abstract summary: We show that item-rating information is more influential than other information types in a collaborative filtering approach. The trust graph-based approaches were found to be more robust to network adversarial attacks due to hard-to-manipulate trust structures.
• Score: 4.833815605196965
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper explores recommender systems in social networks which leverage information such as item rating, intra-item similarities, and trust graph. We demonstrate that item-rating information is more influential than other information types in a collaborative filtering approach. The trust graph-based approaches were found to be more robust to network adversarial attacks due to hard-to-manipulate trust structures. Intra-item information, although sub-optimal in isolation, enhances the consistency of predictions and lower-end performance when fused with other information forms. Additionally, the Weighted Average framework is introduced, enabling the construction of recommendation systems around any user-to-user similarity metric.

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