Chinese word segmentation with a maximum entropy approach

Master's

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Main Author: LOW JIN KIAT
Other Authors: COMPUTER SCIENCE
Format: Theses and Dissertations
Language:English
Published: 2010
Subjects:
Online Access:http://scholarbank.nus.edu.sg/handle/10635/15159
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Institution: National University of Singapore
Language: English
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spelling sg-nus-scholar.10635-151592017-10-21T09:56:10Z Chinese word segmentation with a maximum entropy approach LOW JIN KIAT COMPUTER SCIENCE NG HWEE TOU Multi lingual processing, corpus based modeling of language, machine learning, Chinese Word Segmentation, Maximum Entropy, Noise Elimination Master's MASTER OF SCIENCE 2010-04-08T10:50:39Z 2010-04-08T10:50:39Z 2006-03-08 Thesis LOW JIN KIAT (2006-03-08). Chinese word segmentation with a maximum entropy approach. ScholarBank@NUS Repository. http://scholarbank.nus.edu.sg/handle/10635/15159 NOT_IN_WOS en
institution National University of Singapore
building NUS Library
country Singapore
collection ScholarBank@NUS
language English
topic Multi lingual processing, corpus based modeling of language, machine learning, Chinese Word Segmentation, Maximum Entropy, Noise Elimination
spellingShingle Multi lingual processing, corpus based modeling of language, machine learning, Chinese Word Segmentation, Maximum Entropy, Noise Elimination
LOW JIN KIAT
Chinese word segmentation with a maximum entropy approach
description Master's
author2 COMPUTER SCIENCE
author_facet COMPUTER SCIENCE
LOW JIN KIAT
format Theses and Dissertations
author LOW JIN KIAT
author_sort LOW JIN KIAT
title Chinese word segmentation with a maximum entropy approach
title_short Chinese word segmentation with a maximum entropy approach
title_full Chinese word segmentation with a maximum entropy approach
title_fullStr Chinese word segmentation with a maximum entropy approach
title_full_unstemmed Chinese word segmentation with a maximum entropy approach
title_sort chinese word segmentation with a maximum entropy approach
publishDate 2010
url http://scholarbank.nus.edu.sg/handle/10635/15159
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