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Title: Detecting emotion cause with sequence labeling model
Other Titles: 基于序列标注模型的情绪原因识别方法
Authors: Lee, YM 
Li, S
Huang, CR 
Gao, Wei
Keywords: Sequence labeling
Emotion cause detection
Context feature
Linguistic rule features
Issue Date: 2013
Publisher: 中国中文信息学会 ; 北京信息工程学院
Source: 中文信息学报 (Journal of Chinese information processing), Sept. 2013, v. 27, no. 5, p. 93-99 How to cite?
Journal: 中文信息学报 (Journal of Chinese information processing) 
Abstract: 情绪原因识别是情绪分析中的一个重要研究任务。该任务旨在自动分析出导致某一情绪发生的原因描述。该文将情绪原因识别任务建模为序列标注模型,即将情绪词相关的子句当成序列,进而整体标注出哪些属于原因子句。具体实现中,我们使用条件随机场(CRF)模型进行求解,并结合了基本词特征、词性特征、距离特征、上下文特征及语言学特征等多种特征进行原因识别。实验结果表明,所采用的这些特征对于原因识别都有一定帮助,特别是上下文特征。此外,我们发现在使用类似特征集合的情况下,序列标注模型能够获得比分类模型更好的识别效果。
Emotion cause detection is an important task in the research on emotion analysis.This task aims to detect the cause description of a emotion happening.In this study,we model this task as a sequence labeling problem and predict each related sentence to be in a emotion cause or not.Specifically,we apply the conditional random field(CRF)model to solve this problem with various of features,such as basic word features,POS features,context features and linguistic rule features.Empirical studies demonstrate that these features are effective for the task,especially the context features.Moreover,we find that the sequence labeling model is superior to the classification model when similar features are employed.
ISSN: 1003-0077
Rights: © 2013 中国学术期刊电子杂志出版社。本内容的使用仅限于教育、科研之目的。
© 2013 China Academic Journal Electronic Publishing House. It is to be used strictly for educational and research purposes.
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