Fu Liao

• Large Language Model Embedding for Cold-Start Item Recommendation via Data Augmentation and Regularization

  Open Access•Kangyi Xie, Ayong Ye et al.•ARTICLE•IEEE Transactions on Computational…•2026

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  The cold-start problem constitutes a persistent challenge in recommender systems (RecSys). Recent advances in large language model (LLM) for natural language processing have inspired researchers to utilize their semantic understanding and knowledge extraction capabilities in recommendation tasks. LLM shows clear advantages in addressing cold-start items. However, current methods often rely on direct online LLM inference. This approach causes high…

• Large Language Model Embedding for Cold-Start Item Recommendation via Data Augmentation and Regularization

  Open Access•Kangyi Xie, Ayong Ye et al.•ARTICLE•IEEE Transactions on Computational…•2026

  Añadir item

  The cold-start problem constitutes a persistent challenge in recommender systems (RecSys). Recent advances in large language model (LLM) for natural language processing have inspired researchers to utilize their semantic understanding and knowledge extraction capabilities in recommendation tasks. LLM shows clear advantages in addressing cold-start items. However, current methods often rely on direct online LLM inference. This approach causes high…

Data modeling (1 obras) · Deep learning (1 obras) · Embedding (1 obras) · Language model (1 obras) · Natural language (1 obras) · Recommender system (1 obras) · Recommender Systems and Techniques (1 obras) · Semantic data model (1 obras) · Sentiment Analysis and Opinion Mining (1 obras) · Topic Modeling (1 obras)