EMPIRICAL TEXT MINING FOR GENRE DETECTION

Vasiliki Simaki; Sofia Stamou; Nikos Kirtsis

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Paper

EMPIRICAL TEXT MINING FOR GENRE DETECTION

Topics: Data Mining; Meta-Knowledge Discovery and Representation; User-Centric Systems

In Proceedings of the 8th International Conference on Web Information Systems and Technologies WEBIST - Volume 1, 733-737, 2012 , Porto, Portugal

Authors: Vasiliki Simaki ¹ ; Sofia Stamou ² and Nikos Kirtsis ³

Affiliations: ¹ Patras University, Greece ; ² Patras University and Ionian University, Greece ; ³ Ionian University, Greece

Keyword(s): Genre Detection, Annotation, Human Study.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: In this paper, we report on a preliminary study we carried out for identifying patterns that characterize the genre type of Greek texts. In the course of our study, we address four distinct genre types, we record their observable stylistic elements and we indicate their exploitation for automatic genre-based document classi-fication. The findings of our study demonstrate that texts contain lexical features with discriminative power as far as genre is concerned, however modeling those features so that they can be explored by computer-based applications is still in early stages.

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Paper citation in several formats:

Simaki, V.; Stamou, S. and Kirtsis, N. (2012). EMPIRICAL TEXT MINING FOR GENRE DETECTION. In Proceedings of the 8th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-8565-08-2; ISSN 2184-3252, SciTePress, pages 733-737. DOI: 10.5220/0003956207330737

@conference{webist12,
author={Vasiliki Simaki. and Sofia Stamou. and Nikos Kirtsis.},
title={EMPIRICAL TEXT MINING FOR GENRE DETECTION},
booktitle={Proceedings of the 8th International Conference on Web Information Systems and Technologies - WEBIST},
year={2012},
pages={733-737},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003956207330737},
isbn={978-989-8565-08-2},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 8th International Conference on Web Information Systems and Technologies - WEBIST
TI - EMPIRICAL TEXT MINING FOR GENRE DETECTION
SN - 978-989-8565-08-2
IS - 2184-3252
AU - Simaki, V.
AU - Stamou, S.
AU - Kirtsis, N.
PY - 2012
SP - 733
EP - 737
DO - 10.5220/0003956207330737
PB - SciTePress