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Research on Few-Shot and Zero-Shot Node Classification Using Text Semantics - Based on Text-Attributed Graphs

💡 原文英文，约100词，阅读约需1分钟。
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内容提要

本研究提出了一种文本语义增强（TSA）方法，旨在解决文本属性图中的少样本和零样本节点分类问题。通过引入积极和消极语义匹配技术，TSA显著提高了分类准确率，实验结果表明其在多个数据集上超越了现有基线，准确度提升超过5%。

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标签

node 少样本 文本属性图 文本语义增强 节点分类 零样本
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