Feature-based subjectivity classification of Filipino text
Added Title
International Conference on Asian Language Processing (2012)
IALP 2012
College
College of Computer Studies
Department/Unit
Software Technology
Document Type
Conference Proceeding
Source Title
Proceedings - 2012 International Conference on Asian Language Processing, IALP 2012
First Page
57
Last Page
60
Publication Date
1-1-2012
Abstract
Subjectivity classification classifies whether a text expresses an opinion or not. Though there are already existing works in this field especially for the English Language, no reports have been made if these approaches are indeed effective when adapted to the Filipino language. This research reports a feature-based approach for subjectivity classification using existing classifiers such as Naïve Bayes, Bagging, Multilayer perceptron and Random Forest Tree. Result shows that the Bagging classifier gave the best results with 64.7% accuracy. © 2012 IEEE.
html
Digitial Object Identifier (DOI)
10.1109/IALP.2012.39
Recommended Citation
Regalado, R. J., & Cheng, C. K. (2012). Feature-based subjectivity classification of Filipino text. Proceedings - 2012 International Conference on Asian Language Processing, IALP 2012, 57-60. https://doi.org/10.1109/IALP.2012.39
Disciplines
Software Engineering
Keywords
Subjectivity (Linguistics); Computational linguistics; Filipino language—Semantics
Upload File
wf_yes
