Data sparsity remains a long-standing challenge in recommender systems, and it becomes more severe for methods relying on user-generated content (UGC) such as textual reviews, which capture fine-grained preferences but require more user efforts to produce. As a result, UGC exhibits (1) missing reviews, where interactio...
Hong-Ren Wang, Tian-Jun Wei, Ying-Peng Du et al.· 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
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
This work proposes PLAN (Parallel Liquid-inspired Approximation Network), a lightweight representation learning framework that reformulates continuous liquid-state dynamics into a discretized and parallelizable formulation and acts as a versatile, plug-and-play backbone that generalizes to complex FJSP variants.
D. D. Kannan, Wei Zhang, Jieyi Bi et al.· 0 citations
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