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Fine-grainedly Synthesize Streaming Data Based On Large Language Models With Graph Structure Understanding For Data Sparsity
March 12, 2024, 4:51 a.m. | Xin Zhang, Linhai Zhang, Deyu Zhou, Guoqiang Xu
cs.CL updates on arXiv.org arxiv.org
Abstract: Due to the sparsity of user data, sentiment analysis on user reviews in e-commerce platforms often suffers from poor performance, especially when faced with extremely sparse user data or long-tail labels. Recently, the emergence of LLMs has introduced new solutions to such problems by leveraging graph structures to generate supplementary user profiles. However, previous approaches have not fully utilized the graph understanding capabilities of LLMs and have struggled to adapt to complex streaming data environments. …
abstract analysis arxiv commerce cs.ai cs.cl data e-commerce e-commerce platforms emergence graph labels language language models large language large language models llms performance platforms reviews sentiment sentiment analysis sparsity streaming streaming data type understanding user data
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