Information Extraction Based on Functional Basis and Experimental Study on Automatic Classification

Le résumé fourni par la source

Abstract:In order to provide interdisciplinary patent knowledge for designer in product innovative design process,a Chinese patent text classification method was proposed based on functional basis.Because functional basis has so many categories and the number of training sets for patent text is less,multiple binary classification algorithm and EM semi supervised learning algorithm were adopted to classify Chinese patent text.Compared with the results of naive Bayesian (NB) fully supervised classification experimental,by using the orthogonal experimental design,the selection of features and data sets were considered according to the accuracy of classification,the classifying accuracy rate of the first class reached above 80% which was in accordance with application requirements.This study provided core technologies for the construction of patent knowledge base based on functional basis in product innovative design system.

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