首页> 外文期刊>International journal of data mining, modelling and management >Extracting useful reply-posts for text forum threads summarisation using quality features and classification methods
【24h】

Extracting useful reply-posts for text forum threads summarisation using quality features and classification methods

机译:用质量特征和分类方法提取文本论坛线程汇总的有用回复帖子

获取原文
获取原文并翻译 | 示例

摘要

Text forums threads have a large amount of information furnished by users who discuss on a specific topic. At times, certain thread reply-posts are entirely off-topic, thereby deviating from the main discussion. It negatively affects the user's preference to continue replying to the discussion. Thus, there is a possibility that the user prefers to read certain selected reply-posts that provide a short summary of the topic of the discussion. The objective of the paper is to choose quality reply-posts regarding a topic considered in the initial-post, which also serve a brief summary. We offer an exhaustive examination of the conversational patterns of the threads on the basis of 12 quality features for analysis. These features can ensure selection of relevant reply-posts for the thread summary. Experimental outcomes obtained using two datasets show that the presented techniques considerably enhanced the performance in selecting initial-post replies pairs for text forum threads summarisation.
机译:文本论坛线程在特定主题上讨论的用户提供了大量信息。有时,某些线程回复帖子完全是偏离主题的,从而偏离了主要讨论。它对用户的偏好产生负面影响继续回复讨论。因此,用户可能喜欢阅读提供提供讨论主题的简短摘要的某些所选的回复帖子。本文的目的是选择有关初始职位中审议的主题的质量回复员额,该专题也提供了一个简短的摘要。我们在12个质量特征的基础上,提供了对线程的会话模式的详尽检查。这些功能可以确保线程摘要选择相关的回复帖子。使用两个数据集获得的实验结果表明,所呈现的技术在选择文本论坛线程汇总的初始回复对中的表现显着提高了表现。

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