首页> 外文会议>2013 2nd IAPR Asian Conference on Pattern Recognition >Automatic Elements Extraction of Chinese Web News Using Prior Information of Content and Structure
【24h】

Automatic Elements Extraction of Chinese Web News Using Prior Information of Content and Structure

机译:利用内容和结构的先验信息自动提取中文网络新闻元素

获取原文
获取原文并翻译 | 示例

摘要

We propose a set of efficient processes for extracting all four elements of Chinese news web pages, namely news title, release date, news source and the main text. Our approach is based on a deep analysis of content and structure features of current Chinese news. We take content indicators as the key to recover tree structure of the main text. Additionally, we come up with the concept of Length-Distance Ratio to help improve performance. Our method rarely depends on selection of samples and has strong generalization ability regardless of training process, distinguishing itself from most existing methods. We have tested our approach on 1721 labeled Chinese news pages from 429 web sites. Results show that an 87% accuracy was achieved for news source extraction, and over 95% accuracy for other three elements.
机译:我们提出了一套有效的方法来提取中文新闻网页的所有四个元素,即新闻标题,发布日期,新闻来源和正文。我们的方法基于对当前中国新闻的内容和结构特征的深入分析。我们将内容指标作为恢复正文树结构的关键。此外,我们提出了“长距比”的概念以帮助提高性能。我们的方法很少依赖样本的选择,并且具有很强的泛化能力,而与训练过程无关,这使其与大多数现有方法有所不同。我们已经对来自429个网站的1721个带有中文标签的新闻页面测试了我们的方法。结果表明,新闻源提取的准确性达到87%,其他三个元素的准确性超过95%。

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