用最大均值差异检测词语意义随时间的变化
Word Sense Detection Leveraging Maximum Mean Discrepancy
- 基于最大均值差异筛选语义相关变量
- 可识别词语意义变化并量化演变过程
- 首个将MMD用于词义变迁检测的方法
词义分析对于理解语言和社会背景至关重要。词义变化检测旨在识别和解释词语意义随时间的演变。本文提出MMD-Sense-Analysis，一种新方法，利用最大均值差异（MMD）选择语义有意义的变量，并量化不同时期间的语义变化。该方法既能识别发生意义转变的词语，又能解释其在多个历史时期中的演化过程。据作者所知，这是首次将MMD应用于词义变化检测。实证评估结果证明了该方法的有效性。
原文摘要 · Abstract (English)
Word sense analysis is an essential analysis work for interpreting the linguistic and social backgrounds. The word sense change detection is a task of identifying and interpreting shifts in word meanings over time. This paper proposes MMD-Sense-Analysis, a novel approach that leverages Maximum Mean Discrepancy (MMD) to select semantically meaningful variables and quantify changes across time periods. This method enables both the identification of words undergoing sense shifts and the explanation of their evolution over multiple historical periods. To my knowledge, this is the first application of MMD to word sense change detection. Empirical assessment results demonstrate the effectiveness of the proposed approach.
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