Thai word segmentation with hidden Markov Model and decision tree

Bheganan, Poramin, Nayak, Richi, & Xu, Yue (2009) Thai word segmentation with hidden Markov Model and decision tree. In Theeramunkong, Thanarak (Ed.) Advances in Knowledge Discovery and Data Mining, Springer Berlin / Heidelberg, Bangkok, pp. 74-85.

View at publisher


The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods.

Impact and interest:

3 citations in Scopus
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

487 since deposited on 29 Jan 2010
50 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 30081
Item Type: Conference Paper
Refereed: Yes
Keywords: Hidden Markov Model, Thai Word segmentation, Decision tree
DOI: 10.1007/978-3-642-01307-2_10
ISBN: 9783642013065
ISSN: 1611-3349
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Information Technology
Copyright Owner: Copyright 2009 Springer
Deposited On: 29 Jan 2010 03:03
Last Modified: 17 Jul 2014 07:16

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page