Statistical Framework for Email Discourse Analysis

机译：电子邮件语篇分析的统计框架

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The discourse structure of emails is an important but largely unaddressed problem. Emails or newsgroup messages are usually organized as threads - a strict tree structure with the original message on the top and the responses at the bottom of the tree. Such a tree models the message-response relationship as a parent-child relationship. In addition to the parent-child relationship between an email and response, we claim that a rhetorical relation also exists between them. These rhetorical relations reflect the nature of exchanges and can be used in tasks like thread summarization. In this paper, we present a framework for Email Discourse Analysis and also an algorithm that learns to characterize the rhetorical relationships in an email thread. We present the results of our algorithm on a collection of messages obtained from the newsgroups.

机译：电子邮件的话语结构是一个重要但基本上未解决的问题。电子邮件或新闻组消息通常组织为线程-一种严格的树结构，原始消息位于顶部，响应位于树的底部。这样的树将消息-响应关系建模为父子关系。除了电子邮件和回复之间的父子关系外，我们还声称它们之间也存在修辞关系。这些修辞关系反映了交换的性质，可用于线程摘要之类的任务。在本文中，我们提出了电子邮件话语分析的框架，以及一种学习表征电子邮件线程中修辞关系的算法。我们在从新闻组获得的消息集合上展示算法的结果。

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来源
《8th World Multi-Conference on Systemics, Cybernetics and Informatics(SCI 2004) vol.2: Computing Techniques》|2004年|214-219|共6页
会议地点 OrlandoFL(US)
作者
Sreenivasa P. Sista; S. H. Srinivasan;
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作者单位

Applied Research Group Satyam Computer Services Limited Bangalore 560025, INDIA;

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会议组织
原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
email classification; machine learning; discourse analysis;

机译：电子邮件分类；机器学习话语分析;

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Statistical Framework for Email Discourse Analysis

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