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

Volume

6

fYear

2009

fDate

12-15 July 2009

Firstpage

3511

Lastpage

3515

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICMLC.2009.5212764

Filename

5212764