A Stochastic Technique to Obtain Training Data for Word Segmentation

Unlike western languages, there exists no word boundary in Japanese. This is why we face to hard problems to analyze documents in Japanese very often. More difficulty arises in expertised domains such as medical, mechanical, computer science documents. In this work, we discuss how to obtain pseudo t...

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Veröffentlicht in:Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 Jg. 3; S. 283 - 286
Hauptverfasser: Fukuda, Takuya, Miura, Takao
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Washington, DC, USA IEEE Computer Society 15.09.2009
IEEE
Schriftenreihe:ACM Conferences
Schlagworte:
Computing methodologies > Artificial intelligence > Natural language processing
Computing methodologies > Machine learning
Computing methodologies > Machine learning > Learning paradigms
Computing methodologies > Modeling and simulation > Model development and analysis > Modeling methodologies
Markov Chain Monte Carlo (MCMC) method
Mathematics of computing > Probability and statistics > Probabilistic algorithms
Mathematics of computing > Probability and statistics > Probabilistic reasoning algorithms > Markov-chain Monte Carlo methods
Mathematics of computing > Probability and statistics > Probabilistic reasoning algorithms > Sequential Monte Carlo methods
Mathematics of computing > Probability and statistics > Probabilistic representations > Markov networks
Mathematics of computing > Probability and statistics > Stochastic processes
Mathematics of computing > Probability and statistics > Stochastic processes > Markov processes
Stochastic processes
Stochastic Techniques
Theory of computation > Theory and algorithms for application domains > Machine learning theory > Markov decision processes
Training data
Word Segmentation
Word Segmentation
Stochastic Techniques
Markov Chain Monte Carlo (MCMC) method
ISBN:0769538010, 9780769538013
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Beschreibung
Zusammenfassung:Unlike western languages, there exists no word boundary in Japanese. This is why we face to hard problems to analyze documents in Japanese very often. More difficulty arises in expertised domains such as medical, mechanical, computer science documents. In this work, we discuss how to obtain pseudo test corpus based on Markov process Monte Carlo Method (MCMC), given small amount of test data. In this environment we show nice results using our approach.
ISBN:0769538010
9780769538013
DOI:10.1109/WI-IAT.2009.283