Title :
Support vector based method for acquiring domain specific patents
Author :
Wang, Chen ; Li, Su-Jian
Author_Institution :
Inst. of Comput. Linguistics, Peking Univ., Beijing, China
Abstract :
Patents classification is useful in the management and some other utilities of patent. In this paper, semi-automatic patent classification system was used to solve the problem. Thus, the classification model was built to filter some domain irrelative patents. Because of different optimization target, regression model was used instead of classification model. The goal of the system is filter more domain irrelative patents while remains more domain relative patents. The experimental results demonstrate that an ideal performance could be reached through the adjustment of threshold.
Keywords :
classification; information filtering; patents; regression analysis; support vector machines; domain irrelative patents; domain specific patent; patent filter; regression model; semiautomatic patent classification system; support vector; Computational linguistics; Conference management; Costs; Cybernetics; Electronic mail; Filters; Libraries; Machine learning; Support vector machine classification; Support vector machines; Domain specification; Patent classification; Support vector regression;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212764
