Titlebook: Hybrid Approaches to Machine Translation; Marta R. Costa-jussà,Reinhard Rapp,Bogdan Babych Book 2016 Springer International Publishing Swi

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Dan Han,Pascual Martínez-Gómez,Yusuke Miyaodifferent time nodes based on aggregate data and sequence data. The experimental results show that sequence data is more effective than aggregate data to predict learning results. The prediction AUC of RF model on sequence data is 0.77 at the lowest and 0.83 at the highest, the prediction AUC of CAR

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ility and privacy, for this data while reducing information loss and misuse. The objective of this paper is to use different methods and different anonymization algorithms, like the 1:m-generalization algorithm and Mondrian, and compare them to show which of them maintains data privacy and high util

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Nathan David Green,Zdeněk ?abokrtskyf handwriting documents has difficulty because each row in the document is uneven and very tight between the rows. Those matters cause them overlap. When the line segmented wrongly, the entire character on the line will be not segmented as well. This problem can be eliminate using connectivity test.

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Hybrid Machine Translation Overview,ration at different levels of depth is described starting with system combination techniques and followed by integration strategies led by rule-based and statistical systems. System combination does not involve any hybrid architecture since it combines translation outputs. It can be done with differ