首页> 外文会议>IEEE International Conference on Engineering Technologies and Applied Sciences >Automatic Sinhala News Classification Approach for News Platforms
【24h】

Automatic Sinhala News Classification Approach for News Platforms

机译:新闻平台的自动僧伽罗新闻分类方法

获取原文

摘要

Because of generating various news articles in large scale, online sources moved into an automatic categorization mechanism. This research has been conducted using LDA topic modeling approach and using other classification algorithms to establish a news categorization solution. Sinhala news websites have only few news categories and do not have any relationships or hierarchies between the categories. Therefore, some users require to search manually and find the necessary articles which are in those categories. Purpose of this study is to build a news categorization model with categorization hierarchies for Sinhala news articles. The goals of the models are to identify the most suitable news category for a related news article and develop hierarchies using generated news categories and assign the news articles according to the hierarchical structure. The final experiments and evaluations show that the solution performs well to solve the automatic categorization problem in Sinhala news platforms.
机译:由于在大规模的各种新闻文章中产生了各种新闻文章,在线源迁移到自动分类机制中。本研究已经使用LDA主题建模方法进行,并使用其他分类算法来建立新闻分类解决方案。 Sinhala新闻网站只有很少的新闻类别,并且在类别之间没有任何关系或层次结构。因此,一些用户需要手动搜索并找到在这些类别中的必要文​​章。本研究的目的是为僧伽伽罗新闻文章的分类层次建立新闻分类模型。模型的目标是为相关新闻文章识别最合适的新闻类别,并使用生成的新闻类别开发层次结构,并根据分层结构分配新闻文章。最终的实验和评估表明,该解决方案能够良好地解决Sinhala新闻平台的自动分类问题。

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