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An Experimental Approach for Information Extraction in Multi-party Dialogue Discourse

Published: 26 February 2023 Publication History

Abstract

In this paper, we address the task of information extraction for transcript meetings. Meeting documents are not usually well structured and are lacking formatting and punctuations. In addition, the information are distributed over multiple sentences. We experimentally investigate the usefulness of numerical statistics and topic modelling methods on a real dataset containing multi-part dialogue texts. Such information extraction can be used for different tasks, of which we consider two: contrasting thematically related but distinct meetings from each other, and contrasting meetings involving the same participants from those involving other. In addition to demonstrating the difference between counting and topic modeling results, we also evaluate our experiments with respect to the gold standards provided for the dataset.

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  1. An Experimental Approach for Information Extraction in Multi-party Dialogue Discourse
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            cover image Guide Proceedings
            Computational Linguistics and Intelligent Text Processing: 19th International Conference, CICLing 2018, Hanoi, Vietnam, March 18–24, 2018, Revised Selected Papers, Part I
            Mar 2018
            440 pages
            ISBN:978-3-031-23792-8
            DOI:10.1007/978-3-031-23793-5

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            Springer-Verlag

            Berlin, Heidelberg

            Publication History

            Published: 26 February 2023

            Author Tags

            1. Information extraction
            2. Dialogue texts
            3. Topic modeling
            4. Term weighting

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