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Empirical Text Mining for Genre Detection

Simaki, Vasiliki LU ; Stamou, Sofia and Kirtsis, Nikolaos (2012) In WEBIST 1. p.733-737
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.
Please use this url to cite or link to this publication:
author
; and
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Genre Detection, Annotation, Human Study
host publication
Proceedings of the 8th International Conference on Web Information Systems and Technologies
series title
WEBIST
editor
Krempels, Karl-Heinz and Cordeiro, José
volume
1
pages
733 - 737
publisher
SciTePress
external identifiers
  • scopus:84864878316
ISBN
978-989-8565-08-2
DOI
10.5220/0003956207330737
language
English
LU publication?
no
id
db214761-4297-4c20-abf0-32f2325d4ded
date added to LUP
2017-06-02 19:35:07
date last changed
2022-02-07 05:39:30
@inproceedings{db214761-4297-4c20-abf0-32f2325d4ded,
  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.}},
  author       = {{Simaki, Vasiliki and Stamou, Sofia and Kirtsis, Nikolaos}},
  booktitle    = {{Proceedings of the 8th International Conference on Web Information Systems and Technologies}},
  editor       = {{Krempels, Karl-Heinz and Cordeiro, José}},
  isbn         = {{978-989-8565-08-2}},
  keywords     = {{Genre Detection; Annotation; Human Study}},
  language     = {{eng}},
  pages        = {{733--737}},
  publisher    = {{SciTePress}},
  series       = {{WEBIST}},
  title        = {{Empirical Text Mining for Genre Detection}},
  url          = {{http://dx.doi.org/10.5220/0003956207330737}},
  doi          = {{10.5220/0003956207330737}},
  volume       = {{1}},
  year         = {{2012}},
}