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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Neural Networks Based Detection of Purpose Data in Text
verfasst von : P. Kiran Mayee, Rajeev Sangal, Soma Paul
Erschienen in: Information and Communication Technologies
Verlag: Springer Berlin Heidelberg
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Purpose is an inherent relation in artifact-related text. This information is available as a pair of components, called ‘purpose-action’ and ‘purpose-upon’ in text. This paper presents the Neural Networks as a possible solution to detecting the existence of ‘purpose_action’ in corpus. Two types of Neural Networks, i.e., RBF Networks and Multilayer Perceptron Neural Network have been tried and compared with a Naïve Bayes approach to detection. The corresponding results have been tabulated. The MLP method is found to be more efficient among the two.