计算机工程与应用2011，Vol.47Issue(34)：164-167,4.DOI:10.3778/j.issn.1002-8331.2011.34.046
基于直推式学习的中文情感词极性判别
Determining of polarity of Chinese opinion words based on transductive learning
摘要
Abstract
In recent years, opinion mining has become one of the hottest topics in the text mining field.It aims to discover the author's opinion polarity in texts and thus to provide support for decision-making process based on the public opinion.Up to now,most of the algorithms developed for opinion mining use an opinion word dictionary to identify the opinion words occurring in a sentence or text and then determine the polarity of the sentence or text based on polarities of these words.However,it's not realistic to construct and maintain manually a perfect opinion word dictionary.Therefore,the problem of determining the polarities of Chinese opinion words is investigated, and an algorithm based on transductive learning is proposed to solve the problem.This algorithm uses a few opinion words as seeds and performs polarity transduction from the seeds to other words based on their dictionary interpretations.Compared with supervised learning algorithms, which use the interpretations of the same seeds as the training data,the transduction-based algorithm has obtained an accuracy improvement of about 20%.关键词
态度挖掘/情感词识别/极性判别/直推式学习/词典解释Key words
opinion mining/opinion word identification/polarity determination/transductive learning/dictionary interpretation分类
信息技术与安全科学引用本文复制引用
金宇,朱洪波,王亚强,陈黎,于中华..基于直推式学习的中文情感词极性判别[J].计算机工程与应用,2011,47(34):164-167,4.基金项目
国家自然科学基金重大研究计划项目(No.90409007). （No.90409007）
