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Conference Sep 2026

A graph contrastive learning recommendation algorithm based on variational inference

Recommender systems are essential tools for alleviating information overload by providing personalized suggestions to users. Graph neural networks (GNNs), capable of capturing complex node relationships and higher-order interactions, have emerged as a prominent research direction in recommendation tasks. In this work,...

Chi Ma, Haohao Cao, Hui Hu et al. · 0 citations
Open access Aug 2026

TaSC-LLM: A Large Language Model–Enabled Business Intelligence Framework for Topic Analytics in Live-Streaming E-Commerce Systems

Empirical evaluation of TaSC-LLM shows that the proposed framework achieves strong taxonomy coverage, classification accuracy, and agreement with expert annotations, and suggests that LLM-based reasoning can help convert unstructured user-generated text into interpretable topic measures for downstream empirical and man...

Geng Peng, Xiaoxi Wang, Ruoshi Zhang et al. · 0 citations

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