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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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2
Projecting named entity tags from a resource rich language to a resource poor language
Published 2012“…The method computes the string similarity between the English words and the list of available lexemes in a pre-built lexicon that approximates the best NE mapping.The algorithm has been effectively evaluated using our own terrorism tagged corpus; it achieved satisfactory results in terms of precision, recall, and F-measure.An evaluation of the selected open source NER tool for English is also presented.…”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…An evaluation of the selected open source NER tool for English is also presented.…”
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4
Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…An evaluation of the selected open source NER tool for English is also presented.…”
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5
Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…An evaluation of the selected open source NER tool for English is also presented.…”
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