2010 Fiscal Year Final Research Report
Uncertainty inference by probabilistic models
| Project/Area Number |
20300053
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
SATO Taisuke Tokyo Institute of Technology, 大学院・情報理工学研究科, 教授 (90272690)
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| Co-Investigator(Kenkyū-buntansha) |
KAMEYA Yoshitaka 東京工業大学, 大学院・情報理工学研究科, 助教 (60361789)
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| Project Period (FY) |
2008 – 2010
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| Keywords | 学習と知識獲得 |
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| Research Abstract |
Currently techniques from machine learning and statistical natural language processing are popular in various fields including data-mining and bioinformatics. However they are feature-based and it is difficult to capture interdependent relationships in real data. We have developed a logic-based modeling language PRISM which unifies logical semantics and statistical parameter learning. It separates model description by logical formulas from their probability computation and parameter learning, thereby enabling an expressive yet efficient complex probabilistic modeling.
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