• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Procedia Computer Science >Research on Text Error Detection and Repair Method Based on Online Learning Community
【24h】

Research on Text Error Detection and Repair Method Based on Online Learning Community

机译：基于在线学习社区的文本错误检测与修复方法研究

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The short text in the online learning community is an important source of data in learning analysis. Therefore, the quality of the short text has a significant impact on the study of learning analysis. Due to the large amount of text data in the learning community, manual detection and repair will cost too much. This paper proposes a text detection and repair framework based on an online learning community. It aims to automatically detect and repair various types of semantic errors and grammatical errors that exist in online learning community short texts. The framework utilizes existing text error detection and repair algorithms and integrates them effectively to form a comprehensive detection and repair algorithm. In this paper, the validity of the framework is verified through experiments on the constructed data set. The experimental results show that the framework has high accuracy in automatically detecting and repairing text errors.
机译：在线学习社区中的短文本是学习分析中重要的数据来源。因此，短文本的质量对学习分析的研究有重要影响。由于学习社区中的大量文本数据，手动检测和修复将花费太多。本文提出了一个基于在线学习社区的文本检测和修复框架。它旨在自动检测和修复在线学习社区短文本中存在的各种类型的语义错误和语法错误。该框架利用现有的文本错误检测和修复算法，并将它们有效地集成在一起，以形成一个全面的检测和修复算法。本文通过对构造数据集的实验验证了该框架的有效性。实验结果表明，该框架在自动检测和修复文本错误方面具有很高的准确性。

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