Teachability on Grammatical Inference and its Applications for Natural Language Processing
| Project/Area Number |
21700007
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Fundamental theory of informatics
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| Research Institution | Okayama Prefectural University |
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Principal Investigator |
TAJIMA Yasuhiro Okayama Prefectural University, 情報工学部, 准教授 (00334467)
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| Project Period (FY) |
2009 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2009: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 教示可能性 / 質問による学習 / テキストセグメンテーション / 単純決定性言語 / 文脈自由言語 / 文法推論 / ランダムサンプリング |
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| Research Abstract |
In this study, we developed a new learning algorithm for a subclass of context-free languages. The main result during the supported term is that we showed polynomial time teachability of a subclass of simple deterministic languages. This language class is polynomial time teachable but it would be hard to learn from example based queries in polynomial time. Thus, our result shows a difference between teaching and learning via queries. Next, we applied our algorithm to natural language processing, then we developed a text segmentation algorithm for conversations and showed the performance improvement. In addition, we applied our algorithm to game tree search. Then we showed an improvement of reinforcement learning algorithm for making the evaluation function. We also confirmed the learning performance is improved by our algorithm.
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Report
(3 results)
Research Products
(10 results)
