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    Computer Science Department, Politehnica University of Bucharest
    Research Institute for Artificial Intelligence

    Extraction of Socio-semantic Data from Chat Conversations in Collaborative Learning Communities

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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.

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    Description

    Title : Extraction of Socio-semantic Data from Chat Conversations in Collaborative Learning Communities
    Author(s) : Traian Rebedea, Stefan Trausan-Matu, Costin-Gabriel Chiru
    Abstract : 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.
    Subject : unspecified
    Area : Other
    Language : English
    Year : 2008

    Affiliations Computer Science Department, Politehnica University of Bucharest
    Journal : Times of Convergence Technologies Across Learning Contexts
    Volume : 5192
    Publisher : Springer Berlin Heidelberg
    Pages : 366-377
    Url : http://www.springerlink.com/index/10.1007/978-3-540-87605-2_41
    Doi : 10.1007/978-3-540-87605-2_41

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