| 在线电影评论倾向性分类算法研究 |
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| 引用本文： | 张建刚,彭勤科,康雪姣.在线电影评论倾向性分类算法研究[J].计算机工程与应用,2011,47(11):91-93. |
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| 作者姓名： | 张建刚 彭勤科 康雪姣 |
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| 作者单位： | 1. 西安交通大学机械制造系统工程国家重点实验室,西安,710049;西安交通大学,智能网络与网络安全教育部重点实验室,西安,710049;西安交通大学电信学院,系统工程研究所,西安,710049
2. 西安交通大学机械制造系统工程国家重点实验室,西安,710049;西安交通大学电信学院,系统工程研究所,西安,710049 |
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| 基金项目： | 国家自然科学基金，国家高技术研究发展计划(863) |
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| 摘 要： | 研究网络在线评论的倾向性分类能够及时了解民众对当前事件、热点话题的态度和心理状态,从而为相关领域的决策提供依据.针对网络在线电影评论倾向性分类问题,提出了基于网络词语扩展及属性约简的解决算法,该算法利用相关度测量对垃圾评论进行剔除,针对网络语言自身特点对其属性进行扩展,使用词频和信息增益分两步进行特征选择,构建特征属性...
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| 关 键 词： | 在线评论 属性约简 垃圾评论过滤 支持向量机 倾向性分类 |
| 修稿时间： | |
Research on tendency classification algorithm for online movie comment |
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| ZHANG Jiangang,PENG Qinke,KANG Xuejiao.Research on tendency classification algorithm for online movie comment[J].Computer Engineering and Applications,2011,47(11):91-93. |
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| Authors: | ZHANG Jiangang PENG Qinke KANG Xuejiao |
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| Affiliation: | 1,31.State Key Laboratory for Manufacturing Systems Engineering,Xi’an Jiaotong University,Xi’an 710049,China2.MOE Key Laboratory for Intelligent Networks and Network Security,Xi’an Jiaotong University,Xi’an 710049,China3.System Engineering Institute,School of Electronic and Information,Xi’an Jiaotong University,Xi’an 710049,China |
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| Abstract: | The research on online comments can promptly understand the public’s attitudes and mental states to current events and hot topics,so it can provide basis for the decision-making for the relative fields.In this paper,an algorithm based on extension of network words and feature selection is proposed to solve the tendency of online movie comments.The garbage comments are eliminated using relevancy measurement,and then features are extended according to the characteristics of online comments.The features are selected for classification based on frequency of words and information gain.The results show that after using this method,the accuracy and other indexes of classification are improved. |
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| Keywords: | online comment feature selection garbage comment filter Support Vector Machine（SVM） tendency classification |
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