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A Non-Entity Approach for Intent-Based Classification: A Case Study of Thai News
Author(s)
Damrongrat, Chaianun
Sangkeettrakarn, Chatchawal
Piyatumrong, Apivadee
Trankultaweekoon, Kanokorn
Seekhem, Pachit
Chuangkrud, Piyawat
Date Issued
January 1, 2022
Type
Conference Paper
Abstract
Conjunction and stop words are normally ignored in text classification task that is content-based, such as classifying news into entertainment or sports. However, they are useful in this study, since the content and the intention of the document are independent. This paper studies intent-based classification that specifically desires to classify the author's intention of Thai news article into three intents, 'inform', 'explain', and 'give solution'. These three intents subtly co-exist with the content of the article and thus is our classification challenge. Our experiments confirm that intent-based classification needs a different approach from those techniques used for content-based classification. Accordingly, we propose a new pipeline for Thai intent-based classification such that conjunction and others can play a significant role above entity. Our contributions include (1) proving the need for a new methodology to handle intent-based classification and (2) proposing the Non-Entity data processing approach to managing intent-based classification problems. The proposed methodology shows partially promising results. Nonetheless, flags for enhancement are also discussed in the conclusion for future works.
Citation
19th International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology Ecti Con 2022, 2022