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Titlebook: Discovery Science; 8th International Co Achim Hoffmann,Hiroshi Motoda,Tobias Scheffer Conference proceedings 2005 Springer-Verlag Berlin He

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Training Support Vector Machines via SMO-Type Decomposition Methodspropose a general and flexible selection of the two-element working set. Main theoretical results include 1) a simple asymptotic convergence proof, 2) a useful explanation of the shrinking and caching techniques, and 3) the linear convergence of this method. This analysis applies to any SMO-type imp
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Practical Algorithms for Pattern Based Linear Regression measured by the correlation between the number of occurrences of the pattern in each string, and the numeric attribute value assigned to the string. We present two algorithms based on suffix trees, that can find the optimal substring pattern in .(.) and .(..) time, respectively, where . is the numb
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Named Entity Recognition for the Indonesian Language: Combining Contextual, Morphological and Part-o capturing the contextual, morphological, and part of speech knowledge necessary in the process of recognizing named entities in Indonesian texts. The InNER strategy is one of knowledge engineering: the domain and language specific rules are designed by expert knowledge engineers. After showing in o
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Assisting Scientific Discovery with an Adaptive Problem Solver discovery. Designing tools to assist Scientific Discovery offers a challenging problematic, since the problems studied by scientists are not yet solved, and valid models are not yet available. It is therefore impossible to create a problem solver to simulate a given phenomenon and explain or predic
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