Please use this identifier to cite or link to this item: https://ir.sc.mahidol.ac.th/handle/123456789/596
Title: Co-occurrence-based error correction approach to word segmentation
Authors: Kanlaya Naruedomkul
Keywords: Word segmentation;Co-occurrence;Correction algorithms;Maximal matchings
Issue Date: 2011
Publisher: 24th International Florida Artificial Intelligence Research Society, FLAIRS - 24
Citation: คณิตศาสตร์
Series/Report no.: ;240-244
Abstract: To overcome the problems in Thai word segmentation, a number of word segmentation has been proposed during the long period of time until today. We propose a novel Thai word segmentation approach so called Co-occurrence-Based Error Correction (CBEC). CBEC generates all possible segmentation candidates using the classical maximal matching algorithm and then selects the most accurate segmentation based on co-occurrence and an error correction algorithm. CBEC was trained and evaluated on BEST 2009 corpus. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.
Description: Scopus
URI: https://ir.sc.mahidol.ac.th/handle/123456789/596
ISSN: 978-157735501-4
Appears in Collections:Mathematics: International Proceedings

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.