Scoring-thresholding pattern based text classifier

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.

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Abstract

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.

Impact and interest:

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ID Code: 59008
Item Type: Conference Paper
Refereed: No
Keywords: Text classification, Pattern mining, Scoring, Thresholding
DOI: 10.1007/978-3-642-36546-1_22
ISBN: 978-3-642-36545-4
ISSN: 978-3-642-36546-1
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 Springer-Verlag Berlin, Heidelberg
Copyright Statement:

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or Lecture Notes in Computer Science
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Deposited On: 17 Apr 2013 05:17
Last Modified: 14 Jul 2013 21:54

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