EMPIRICAL TEXT MINING FOR GENRE DETECTION

Vasiliki Simaki; Sofia Stamou; Nikos Kirtsis

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

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.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 18.116.23.59

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

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