| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Research Abstract |
Recently the approaches generically called "distributional learning" have been making a great success in the learning of context-free languages. This research project revealed the exact mathematical symmetry of the two types of distributional learning approaches. Based on this observation, we gave a uniform view of the existing distributional learning algorithms and designed an algorithm which integrates existing distributional learning algorithms in it. The obtained algorithm is stronger than other distributional learners for context-free languages. Moreover, we showed that the techniques can be applied to different grammar formalisms that are more powerful than context-free grammars in a uniform way. We also proposed an algorithm that learns certain context-free languages from positive examples only with high probability and accuracy.
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