Subjectivity classification of Filipino text withfeatures based on term frequency - Inverse document frequency

Subjectivity classification of Filipino text withfeatures based on term frequency - Inverse document frequency

Subjectivity classification classifies a given document if it contains subjective information or not, or identifies which portions of the document are subjective. This research reports a machine learning approach on document-level and sentence-level subjectivity classification of Filipino texts usin...

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Bibliographic Details
Main Authors: Regalado, Ralph Vincent J., Chua, Jenina L., Co, Justin L., Tiam-Lee, Thomas James Z.
Format: text
Published: Animo Repository 2013
Subjects:
Subjectivity (Linguistics)
Computational linguistics
Filipino language—Semantics
Machine learning
Computer Sciences
Online Access:https://animorepository.dlsu.edu.ph/faculty_research/13019
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Institution: De La Salle University
Description
Summary:Subjectivity classification classifies a given document if it contains subjective information or not, or identifies which portions of the document are subjective. This research reports a machine learning approach on document-level and sentence-level subjectivity classification of Filipino texts using existing machine learning algorithms such as C4.5, Naïve Bayes, k-Nearest Neighbor, and Support Vector Machine. For the document-level classification, result shows that Support Vector Machines gave the best result with 95.06% accuracy. While for the sentence-level classification, Naïve Baves gave the best result with 58.75% accuracy.

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