Hierarchical text classification using Relative Inverse Document Frequency

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Published: Apr 20, 2021
DOI: https://doi.org/10.37936/ecti-cit.2021152.240515
Keywords:
Hierarchical Text classification Term weighting Hierarchical categories Relative inverse documents frequency (IDFr)

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Boonthida Chiraratanasopha
Faculty of Science Technology and Agriculture, Yala Rajabhat University, Thailand
Thanaruk Theeramunkong
School of ICT, Sirindhorn International Institute of Technology, Thammasat University, Thailand
Salin Boonbrahm
School of Informatics, Walailak University, Thailand

Abstract

Automatic hierarchical text classification has been a challenging and in-needed task with an increasing of hierarchical taxonomy from the booming of knowledge organization. The hierarchical structure identifies the relationships of dependence between different categories in which can be overlapped of generalized and specific concepts within the tree. This paper presents the use of frequency of the occurring term in related categories among the hierarchical tree to help in document classification. The four extended term weighting of Relative Inverse Document Frequency (IDFr) including its located category, its parent category, its sibling categories and its child categories are exploited to generate a classifier model using centroid-based technique. From the experiment on hierarchical text classification of Thai documents, the IDFr achieved the best accuracy and F-measure as 53.65% and 50.80% in Top-n features set from family-based evaluation in which are higher than TF-IDF for 2.35% and 1.15% in the same settings, respectively.

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How to Cite
[1]
B. Chiraratanasopha, T. Theeramunkong, and S. Boonbrahm, “Hierarchical text classification using Relative Inverse Document Frequency”, ECTI-CIT Transactions, vol. 15, no. 2, pp. 166–176, Apr. 2021.
Issue
Vol. 15 No. 2 (2021): ECTI Transactions on CIT (Aug 2021)
Section
Research Article
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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