A Kind of Text Classification Method Based on Fuzzy Vector Space Model and Neural Networks

Jun Hui Pan; Hui Li

doi:10.4028/www.scientific.net/AMM.347-350.2856

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 347-350A Kind of Text Classification Method Based on...

A Kind of Text Classification Method Based on Fuzzy Vector Space Model and Neural Networks

Abstract:

A kind of text classification method based on fuzzy vector space model and neural networks is proposed in the paper according to the problems that a text can be belongs to many types during the text classification. Fuzzy theory is adopted in the method to look the occurring position of feature items in text on as the important degree (membership) reflecting text subject, and fully considered the position information while the features are extracted, thus the fuzzy feature vectors are constructed, as a result, the text classification is close to the manual classification method. The established networks are constituted of input layer, hidden layer and output layer, the input layer completes the inputs of classification samples, hidden layer extracts the implicit pattern features of input samples, the output layer is used to output the classification results. Finally the effectiveness of this method is proved by some documents of Wan Fang data in experimental section. (Abstract)

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Periodical:

Applied Mechanics and Materials (Volumes 347-350)

Pages:

2856-2859

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.347-350.2856

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Online since:

August 2013

Authors:

Jun Hui Pan, Hui Li

Keywords:

Feature Extracted, Fuzzy Feature Vector, Fuzzy Vector Space, Membership, Neural Network (NN), Text Classification

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