Recommender systems model users and rank candidates within individual provider boundaries, fragmenting user context across services. User agents offer a different interaction model: they can act on the user’s behalf and seek recommendations across providers, but only if user context can travel with them. We present Tas...
Rong-Jie Zhu, Tian-Jun Wei, Cong Zhang et al.· Proceedings of the 20th ACM...· 0 citations
Sequential recommendation (SR) systems are widely deployed across modern online platforms, and have been shown to be vulnerable to poisoning attacks. Such attacks inject fabricated user sequences into training data to promote target items. Existing methods achieve stealthiness by enforcing surface-level similarity to g...
Hang-Chang Zhou, Hong-Xu Ma, Hui Fang et al.· Proceedings of the 20th ACM...· 0 citations
Leveraging auxiliary textual data can help with user profiling and item characterization in recommender systems (RSs). However, incomplete user and item descriptions limit the potential of textual information. To this end, we propose a graph-aware convolutional large language model (LLM) method, eliciting LLMs to summa...
Ying-Peng Du, Ziteng Wang, Zhu Sun et al.· ACM Transactions on Informat...· 0 citations
Sequential recommendation (SR) systems are widely deployed across modern online platforms, and have been shown to be vulnerable to poisoning attacks. Such attacks inject fabricated user sequences into training data to promote target items. Existing methods achieve stealthiness by enforcing surface-level similarity to g...
Hang-Chang Zhou, Hong-Xu Ma, Hui Fang et al.· Proceedings of the 20th ACM...· 0 citations
Tasteprint is presented, a local-first plugin framework that combines a cold-start questionnaire with authorized activity from 13 shopping, entertainment, social, and conversational services to build portable recommendation context and requires neither a new model nor a cloud profile service.
Rong-Jie Zhu, Tian-Jun Wei, Cong Zhang et al.· Proceedings of the 20th ACM...· 0 citations
A novel supervised feature selection method named PRISM is proposed, which leverages product manifold to theoretically disentangle class-specific features from the shared structure and provides a theoretical guarantee by deriving an asymptotic convergence proof under the product manifold setting, guaranteeing the relia...
Mao Li, Zhi-Long Mi, Yingpeng Du et al.· Proceedings of the 32nd ACM...· 0 citations
Large Language Models (LLMs) have shown strong potential for sequential reasoning, creating new opportunities for next Point-of-Interest (POI) recommendation. However, applying LLMs to POI prediction remains challenging due to the modality gap between textual semantics and continuous spatio-temporal signals. Existing r...
Nan Jiang, Haitao Yuan, Tian-Jun Wei et al.· Proceedings of the 32nd ACM...· 0 citations
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