Parsing Thai Social Data: A New Challenge for Thai NLP

dc.contributor.authorSattaya Singkul
dc.contributor.authorBorirat Khampingyot
dc.contributor.authorNattasit Maharattamalai
dc.contributor.authorSupawat Taerungruang
dc.contributor.authorTawunrat Chalothorn
dc.date.accessioned2025-07-21T06:02:19Z
dc.date.issued2019-10-01
dc.description.abstractDependency parsing (DP) is a task that analyzes text for syntactic structure and relationship between words. DP is widely used to improve natural language processing (NLP) applications in many languages such as English. Previous works on DP are generally applicable to formally written languages. However, they do not apply to informal languages such as the ones used in social networks. Therefore, DP has to be researched and explored with such social network data. In this paper, we explore and identify a DP model that is suitable for Thai social network data. After that, we will identify the appropriate linguistic unit as an input. The result showed that, the transition based model called, improve Elkared dependency parser outperform the others at UAS of 81.42%.
dc.identifier.doi10.1109/isai-nlp48611.2019.9045639
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/8782
dc.subjectDependency grammar
dc.subject.classificationNatural Language Processing Techniques
dc.titleParsing Thai Social Data: A New Challenge for Thai NLP
dc.typePreprint

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