首页> 外文会议>2011 IEEE Electronics, Robotics and Automotive Mechanics Conference >Optimizing Feature Selection Techniques for Sentiment Classification
【24h】

Optimizing Feature Selection Techniques for Sentiment Classification

机译:情感分类的特征选择技术优化

获取原文

摘要

A hybrid feature selection method is proposed to distinguish the salient features that allow identifying the viewpoint underlying a text review, that is, to determine its sentiment polarity. This method makes use of fundamental pre-processing tasks known as filter and wrapper techniques. The effectiveness of this approach is demonstrated on a data set where each document is represented by two distinct feature vectors based on two different sets of rules.
机译:提出了一种混合特征选择方法来区分显着特征,这些显着特征允许识别文本审阅的基础观点,即确定其情感极性。此方法利用了称为过滤器和包装器技术的基本预处理任务。这种方法的有效性在数据集上得到了证明,其中每个文档都基于两个不同的规则集由两个不同的特征向量表示。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号