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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| Vydané v: | Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03 Ročník 3; s. 283 - 286 |
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| Hlavní autori: | , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
Washington, DC, USA
IEEE Computer Society
15.09.2009
IEEE |
| Edícia: | ACM Conferences |
| Predmet: |
Computing methodologies
> Modeling and simulation
> Model development and analysis
> Modeling methodologies
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
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| ISBN: | 0769538010, 9780769538013 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | 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. |
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| ISBN: | 0769538010 9780769538013 |
| DOI: | 10.1109/WI-IAT.2009.283 |

