Segmentation and Clustering of Textual Sequences: a Typological Approach

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State: Public
Version: author
Serval ID
serval:BIB_01C7B253DB80
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Title
Segmentation and Clustering of Textual Sequences: a Typological Approach
Title of the conference
Recent Advances in Natural Language Processing. International Conference (RANLP 8 : Hissar : 2011). Proceedings
Author(s)
Cocco C., Pittier R., Bavaud F., Xanthos A.
Publisher
Incoma
Address
Shoumen
ISBN
1313-8502
Publication state
Published
Issued date
2011
Peer-reviewed
Oui
Editor
Angelova G., Bontcheva K., Mitkov R., Nikolov N.
Pages
427-433
Language
english
Abstract
The long term goal of this research is to develop a program able to produce an automatic segmentation and categorization of textual sequences into discourse types. In this preliminary contribution, we present the construction of an algorithm which takes a segmented text as input and attempts to produce a categorization of sequences, such as narrative, argumentative, descriptive and so on. Also, this work aims at investigating a possible convergence between the typological approach developed in particular in the field of text and discourse analysis in French by Adam (2008) and Bronckart (1997) and unsupervised statistical learning.
Keywords
fuzzy clustering, discourse types, part-of-speech distributions
Create date
27/09/2011 16:23
Last modification date
20/08/2019 13:24
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