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首页> 外文会议>Times of Convergence: Technologies Across Learning Contexts >Extraction of Socio-semantic Data from Chat Conversations in Collaborative Learning Communities
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Extraction of Socio-semantic Data from Chat Conversations in Collaborative Learning Communities

机译：从协作学习社区的聊天会话中提取社会语义数据

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Online collaboration among communities of practice using text-based tools, such as instant messaging, forums and web logs (blogs), has become very popular in the last years, but it is difficult to automatically analyze all their content due to the problems of natural' language understanding software. However, useful socio-semantic data can be retrieved from a chat conversation using ontology-based text mining techniques. In this paper, a novel approach for detecting several kinds of semantic data from a chat conversation is presented. This method uses a combination of a dialogistic, socio-cultural perspective and of classical knowledge-based text processing methods. Lexical and domain ontologies are used. A tool has been developed for the discovery of the most important topics and of the contribution of each participant in the conversation. The system also discovers new, implicit references among the utterances of the chat in order to offer a multi-voiced representation of the conversation. The application offers a panel for visualizing the threading of the subjects in the chat and the contributions function. The system was experimented on chat sessions of small groups of students participating in courses on Human-Computer Interaction and Natural Language Processing in "Politehnica" University of Bucharest, Romania.
机译：在过去的几年中，使用即时通讯，论坛和网络日志（博客）等基于文本的工具在实践社区之间进行在线协作非常流行，但是由于自然问题，很难自动分析其所有内容语言理解软件。但是，可以使用基于本体的文本挖掘技术从聊天对话中检索有用的社会语义数据。本文提出了一种从聊天对话中检测几种语义数据的新颖方法。这种方法结合了对话，社会文化的观点和基于经典知识的文本处理方法的结合。使用词法和领域本体。已经开发了一种工具，用于发现最重要的主题以及对话中每个参与者的贡献。系统还可以在聊天的话语中发现新的隐式引用，以提供对话的多声音表示。该应用程序提供了一个面板，用于可视化聊天和贡献功能中主题的主题。该系统在罗马尼亚布加勒斯特大学“ Politehnica”大学的人机交互和自然语言处理课程的小学生聊天会话中进行了实验。

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