| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2015: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Outline of Final Research Achievements |
In this research, I solved the domain adaptation for word sense disambiguation by using the learning method under the assumption of covariate shift. The key point of this approach is how to estimation of the probability density ratio, and how to conduct the weighted learning. For the first problem, I adopt unconstrained least squares importance fitting (uLSIF). In this research, I showed that a linear kernel is better than a Gaussian kernel used as the basis function generally. Furthermore, I proposed to use 3 kinds of discrete values as a weight. For the second problem, I showed that SVM also is available but the maximum entropy method. Furthermore, I combined the kernel function, the weighted learning and discrete weights.
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