主观句识别的工作在诸如情感分类和意见摘要等意见挖掘系统中占有很重要的地位。在该文中,我们提出一种基于情感密度的模糊集合分类器以识别汉语主观句。首先,我们利用优势率方法从训练语料中抽取主观性线索词;然后,为了能更好的表达一个句子的主观性,我们利用抽取出的主观性线索词计算出每个句子的情感密度;最后,我们结合情感密度的特点实现了一个三角形隶属度函数的模糊集合分类器以识别主观句。我们在NTCIR-6中文数据中做了两组实验。实验结果表明我们的方法具有一定的可行性。
Abstract
Subjectivity recognition plays an important role in many opinion mining systems such as sentiment classifiers and opinion summarization systems. In this paper, we present a sentiment density based fuzzy sets classifier for Chinese subjectivity classification. In this study, we first employ the odds ratio technique to extract subjective cues from training data. Then, we calculate sentiment density using the extracted subjective cues to represent sentence subjectivity. Finally, we implement a triangular fuzzy sets classifier with sentiment density as features for subjectivity classification. We conduct two experiments on the NTCIR-6 Chinese opinion data, showing the feasibility of the proposed method.
关键词
主观句识别 /
情感密度 /
模糊集合 /
优势率
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Key words
subjectivity recognition /
sentiment density /
fuzzy sets /
odds ratio
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参考文献
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脚注
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基金
国家自然科学基金(60973081,61170148);黑龙江省人力资源和社会保障厅留学人员科技活动项目(1154hz26);黑龙江大学研究生创新科研项目重点项目(YJSCX2014-017HLJU)
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