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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: Proceedings of the 24th International Florida Artificial Intelligence Research Society, FLAIRS - 24 2011; 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
ISSN: 978-157735501-4
Appears in Collections:Mathematics: International Proceedings

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