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
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
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
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
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
