mlsanityData to 7 Oct 2026

FROG: Effective Friend Recommendation in Online Games via Modality-aware User Preferences

arXiv 2504.09428 ↗First posted 13 Apr 2025cs.SI cs.AI cs.IRcited by 1

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Abstract (arXiv)

Due to the convenience of mobile devices, the online games have become an important part for user entertainments in reality, creating a demand for friend recommendation in online games. However, none of existing approaches can effectively incorporate the multi-modal user features (e.g., images and texts) with the structural information in the friendship graph, due to the following limitations: (1) some of them ignore the high-order structural proximity between users, (2) some fail to learn the pairwise relevance between users at modality-specific level, and (3) some cannot capture both the local and global user preferences on different modalities. By addressing these issues, in this paper, we propose an end-to-end model FROG that better models the user preferences on potential friends. Comprehensive experiments on both offline evaluation and online deployment at Tencent have demonstrated the superiority of FROG over existing approaches.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 24 of its 55 references that are in the map. First posted on arXiv 13 Apr 2025.

Builds on

24 of 55 references.

References · 24

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12 more
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Citing papers per year: 2025: 1.

1 paper.

  1. 2025Heterogeneous Influence Maximization in User Recommendationcited by 1