Scoring-thresholding pattern based text classifier


Autoria(s): Bijaksana, Moch Arif; Li, Yuefeng; Algarni, Abdulmohsen
Contribuinte(s)

Selamat, Ali

Nguyen, Ngoc Thanh

Haron, Habibollah

Data(s)

2013

Resumo

A big challenge for classification on text is the noisy of text data. It makes classification quality low. Many classification process can be divided into two sequential steps scoring and threshold setting (thresholding). Therefore to deal with noisy data problem, it is important to describe positive feature effectively scoring and to set a suitable threshold. Most existing text classifiers do not concentrate on these two jobs. In this paper, we propose a novel text classifier with pattern-based scoring that describe positive feature effectively, followed by threshold setting. The thresholding is based on score of training set, make it is simple to implement in other scoring methods. Experiment shows that our pattern-based classifier is promising.

Identificador

http://eprints.qut.edu.au/59008/

Publicador

Springer Berlin Heidelberg

Relação

DOI:10.1007/978-3-642-36546-1_22

Bijaksana, Moch Arif, Li, Yuefeng, & Algarni, Abdulmohsen (2013) Scoring-thresholding pattern based text classifier. In Selamat, Ali, Nguyen, Ngoc Thanh, & Haron, Habibollah (Eds.) Intelligent Information and Database Systems : 5th Asian Conference, ACIIDS 2013, Kuala Lumpur, Malaysia, March 18-20, 2013, Proceedings, Part I, Springer Berlin Heidelberg, Istana Hotel, Kuala Lumpur, Malaysia, pp. 206-215.

Direitos

Copyright 2013 Springer-Verlag Berlin, Heidelberg

Conference proceedings published, by Springer Verlag, will be available via SpringerLink. http://www.springerlink.com or Lecture Notes in Computer Science http://www.springer.de/comp/lncs/

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #Text classification #Pattern mining #Scoring #Thresholding
Tipo

Conference Paper