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Sentiment Target Extraction Based on CRFs with Multi-features for Chinese Microblog

机译：基于多特征CRF的中文微博情感目标提取

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摘要

Sentiment target extraction on Chinese microblog has attracted increasing research attention. Most previous work relies on syntax, such as automatic parse trees, which are subject to noise for informal text such as microblog. In this paper, we propose a modified CRFs model for Chinese microblog sentiment target extraction. This model see the sentiment target extraction as a sequence-labeling problem, incorporating the contextual information, syntactic rules and opinion lexicon into the model with multi-features. The major contribution of this method is that it can be applied to the texts in which the targets are not mentioned in the sequence. Experimental results on benchmark datasets show that our method can consistently outperform the state-of-the-art methods.
机译：中国微博中情感目标的提取引起了越来越多的研究关注。以前的大多数工作都依赖于语法，例如自动分析树，这些语法会受到诸如微博之类的非正式文本的干扰。在本文中，我们提出了一种用于中文微博情感目标提取的改进的CRFs模型。该模型将情感目标提取视为一个序列标签问题，将上下文信息，句法规则和意见词典纳入具有多种功能的模型中。该方法的主要贡献在于它可以应用于顺序中未提及目标的文本。在基准数据集上的实验结果表明，我们的方法可以始终胜过最先进的方法。

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  • 来源
  • 会议地点 Suzhou(CN)
  • 作者

    Bingfeng Chen; Zhifeng Hao; Ruichu Cai; Wen Wen; Shenzhi Du;

  • 作者单位

    Faculty of Computer Science, Guangdong University of Technology, Guangzhou, China;

    Faculty of Computer Science, Guangdong University of Technology, Guangzhou, China,School of Mathematics and Big Data, Foshan University, Foshan, China;

    Faculty of Computer Science, Guangdong University of Technology, Guangzhou, China;

    Faculty of Computer Science, Guangdong University of Technology, Guangzhou, China;

    Faculty of Computer Science, Guangdong University of Technology, Guangzhou, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    CRFs; Multi-features; Sentiment target extraction; Sentiment analysis;

    机译：CRF；多种功能；情感目标提取；情绪分析;

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