Nozomu Onodera
ABSTRACT
In this paper, we address a novel social recommendation for users who have no interactions with items (unobserved users). This task can provide many applications such as recommendations for cold-start users after the first sign-up and targeted advertising, thus, it seems to be extremely meaningful. However, existing social recommendation methods are unsuitable for this task since they assume that all users have interactions with items or cannot recommend more effectively than MostPopular recommendation. Towards this end, we propose Unobserved user-oriented Graph Social Recommendation (UGSR), which learns the preferences of unobserved users and provides richer recommendations than MostPopular recommendation. The popularity-aware graph convolutional network, which is carefully designed for this task, simultaneously considers some user-item interactions, social relations, and item popularity for the effective user and item modeling.
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Index Terms
- Popularity-Aware Graph Social Recommendation for Fully Non-Interaction Users
Recommendations
Interactive Social Recommendation
CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge ManagementSocial recommendation has been an active research topic over the last decade, based on the assumption that social information from friendship networks is beneficial for improving recommendation accuracy, especially when dealing with cold-start users who ...
Social recommendation based on users’ attention and preference
AbstractAttention is the behavioral and cognitive process of selectively concentrating on small fraction of information while ignoring other perceivable information. Thus, user’s attention will influence his decision on the consumption and ...
Quaternion-based knowledge graph neural network for social recommendation
AbstractIn recent years, the surge in the number of users in recommender systems has brought unprecedented opportunities and challenges to research on recommender systems. The development of the graph neural network makes social recommendation ...
Highlights- We propose a novel quaternion-based knowledge graph neural network for social recommendation (QSoR).
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