该文提出了一种新的基于HowNet相似度计算的词汇倾向性识别方法。该方法首先利用HowNet中的“良”、“莠”极性义原进行一种新的相似度——极性相似度的计算,再计算出词汇的极性值,进而识别出词汇的极性倾向。大量实验证明了该方法能够有效地区分词汇的极性,并且在第一届中文倾向性分析评测(COAE2008)比赛中取得了很好的效果。
Abstract
In this paper, a new method of Chinese words semantic orientation computing based on How-net is presented. It uses the subjective sememe of How-net to calculate a new similarity which is called polar similarity, and the the word semantic orientation is determined by the plarity value. Experimental results show that the proposed methods can identify the word semantic orientation effectively, performing best in the subtasks of subjective words polarity analysis of the First Chinese Opinion Analysis Evaluation (COAE2008).
Key wordscomputer application; Chinese information processing; subjective sememe; polarity similarity; polarity value
关键词
计算机应用 /
中文信息处理 /
极性义原 /
极性相似度 /
极性值
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Key words
computer application /
Chinese information processing /
subjective sememe /
polarity similarity /
polarity value
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参考文献
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[7] 朱嫣岚,闵锦,周雅倩,黄萱菁,吴立德.基于HowNet的词汇语义倾向计算[J]. 中文信息学报,2006,20(1): 14-20.
[8] HowNet R. HowNet's Home Page[DB/OL]. http://www.keenage.com.
[9] 李峰,李芳.中文词语语义相似度计算-基于知网2000[J],中文信息学报,2007,21(1):99-105.
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基金
国家自然科学基金重大研究计划资助项目(9092000);国家自然科学基金资助项目(60773167);973国家重点基础研究发展计划资助项目(2007CB310804);教育部/国家外国专家局高等学校学科创新引智计划资助项目(B07042);国家十一五科技支撑计划资助项目(2006BAK11B03)
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