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Overview of Topic-based Chinese Message Polarity Classification in SIGHAN 2015

机译:SIGHAN 2015中基于主题的中文消息极性分类概述

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摘要

This paper presents the overview of Topic-based Chinese Message Polarity Classification in SIGHAN 2015 bake-off. Topic-based message polarity classification plays an important role in sentiment analysis, information extraction, event tracking, and other related research areas. This task is designed to evaluate the techniques for Chinese message polarity classification towards a given topic. The task organizers manually constructed 25 topics together with 24,374 corresponding messages which were annotated to construct the training and testing datasets. The evaluation results achieved by the participators provide good suggestion for the future research.
机译:本文概述了SIGHAN 2015大会中基于主题的中文消息极性分类。基于主题的消息极性分类在情感分析,信息提取,事件跟踪和其他相关研究领域中起着重要作用。此任务旨在评估针对给定主题的中文消息极性分类技术。任务组织者手动构建了25个主题以及24,374条相应的消息,并对其进行了注释,以构建训练和测试数据集。参加者取得的评估结果为今后的研究提供了很好的建议。

著录项

  • 来源
  • 会议地点 Beijing(CA)
  • 作者单位

    College of Mathematics and Computer Science, Fuzhou University, China;

    School of Information Science and Technology, University of International Relations;

    National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences;

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

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