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Co-Occurrence-Based Error Correction Approach to Word Segmentation

Co-Occurrence-Based Error Correction Approach to Word Segmentation

Ekawat Chaowicharat, Kanlaya Naruedomkul
Copyright: © 2012 |Pages: 11
ISBN13: 9781613504475|ISBN10: 1613504470|EISBN13: 9781613504482
DOI: 10.4018/978-1-61350-447-5.ch023
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MLA

Chaowicharat, Ekawat, and Kanlaya Naruedomkul. "Co-Occurrence-Based Error Correction Approach to Word Segmentation." Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches, edited by Chutima Boonthum-Denecke, et al., IGI Global, 2012, pp. 354-364. https://doi.org/10.4018/978-1-61350-447-5.ch023

APA

Chaowicharat, E. & Naruedomkul, K. (2012). Co-Occurrence-Based Error Correction Approach to Word Segmentation. In C. Boonthum-Denecke, P. McCarthy, & T. Lamkin (Eds.), Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches (pp. 354-364). IGI Global. https://doi.org/10.4018/978-1-61350-447-5.ch023

Chicago

Chaowicharat, Ekawat, and Kanlaya Naruedomkul. "Co-Occurrence-Based Error Correction Approach to Word Segmentation." In Cross-Disciplinary Advances in Applied Natural Language Processing: Issues and Approaches, edited by Chutima Boonthum-Denecke, Philip M. McCarthy, and Travis Lamkin, 354-364. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-447-5.ch023

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Abstract

A number of word segmentation algorithms have been offered in the past; however, there is still room for improvement. Co-occurrence-Based Error Correction (CBEC), the proposed approach in this chapter, is a novel Thai word segmentation approach that was designed to provide accurate segmentation results based on context and purpose. CBEC quickly segments the input string using any available algorithm; maximal matching was used in the experiment. Next, CBEC checks its segmentation output against an error risk data bank to determine if there is any error risk. The error risk data bank is developed based on a training corpus. The current version of the error risk bank was based on the training corpus available at BEST 2009. Then, CBEC re-segments the input string using the co-occurrence score of the word sequence to ensure the accuracy of the segmentation result.

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