• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.857-864
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• 2015

By Wikipedia, data mining is the computational process of discovering patterns in huge data sets involving methods at the intersection of association rule, decision tree, clustering, artificial intelligence, machine learning. Clustering or cluster analysis is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. The similarity measures being used in the clustering may be classified into various types depending on the characteristics of data. In this paper, we computed bounds for similarity measures based on the probabilistic interestingness measure with partially marginal probability such as Peirce I, Peirce II, Cole I, Cole II, Loevinger, Park I, and Park II measure. We confirmed the absolute value of Loevinger measure wasthe upper limit of the absolute value of any other existing measures. Ordering of other measures is determined by the size of concurrence proportion, non-simultaneous occurrence proportion, and mismatch proportion.

• Journal of Industrial Convergence
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• v.2 no.1
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• pp.23-46
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• 2004

Tax exhaustion effect hypothesis says that firms with low expected marginal tax rates on their interest deductions employ less debt in their capital structure. We use logit analysis to study how financing decision is related to tax after controlling non tax effects. We treat non debt tax shields as proxy of marginal corporate tax rates which affect the probability of using the deductibility of debt tax shields and empirically test the tax effect on financing decision in Korea. In conclusion, we provide evidence that debt financing is positively related to tax in the former sub-period. This results partially support for tax exhaustion effect hypothesis and low tax rate firms have lower debt levels than high tax rate firms.