KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Author: search.filters.author.Damrongrat, ChaianunSubject: search.filters.subject.context independence

Search Results

Now showing 1 - 1 of 1
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    A Non-Entity Approach for Intent-Based Classification: A Case Study of Thai News
    (2022-01-01)
    Damrongrat, Chaianun
    ;
    Sangkeettrakarn, Chatchawal
    ;
    Piyatumrong, Apivadee
    ;
    Trankultaweekoon, Kanokorn
    ;
    Seekhem, Pachit
    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.