面向意见挖掘的领域自适应:多极词研究

M. Marchand, Romaric Besançon, O. Mesnard, Anne Vilnat
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引用次数: 3

摘要

意见的表达取决于领域。例如,有些词,在这里被称为多极词,在不同的域有不同的极性。因此,如果没有自适应,在一个领域上训练并在另一个领域上测试的分类器将不会表现良好。本文研究了多极词对自动意见分类领域自适应的影响。我们还提出了一种探索性的方法来检测它们,而不需要在目标域中使用任何标签。我们还展示了这些多极词如何在开放域语料库中改进意见分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Domain Adaptation for Opinion Mining: A Study of Multipolarity Words
Expression of opinion depends on the domain. For instance, some words, called here multi-polarity words, have dierent polarities across domain. Therefore, a classifier trained on one domain and tested on another one will not perform well without adaptation. This article presents a study of the influence of these multi-polarity words on domain adaptation for automatic opinion classification. We also suggest an exploratory method for detecting them without using any label in the target domain. We show as well how these multi-polarity words can improve opinion classification in an open-domain corpus.
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