1. School of Information Science and Technology,Beijing Forestry University,Beijing 100083,China
2. School of Automation,Beijing Information Science and Technology University,Beijing 100192,China
3. Network Center,Beihang University,Beijing 100191,China
Abstract：Patents and journals belong to different knowledge organization systems. To achieve the crossbrowsing and crossretrieval between journal literature and patents，the mapping problem between two classifications Chinese Library Classification (CLC) and International Patent Classification (IPC), must be addressed. According to the survey of the existing methods of classification mapping, this paper discussed a method to achieve the mapping between CLC and IPC based on machine learning. The learner was got by training the corpus identified by the CLC category, with which to classify the corpus identified by the IPC category. The mapping relations can be found after analyzing the classification results. And the comparison experiment proves the effectiveness of this method.
靳雪茹 齐建东 王立臣 周林志. 基于机器学习的类目映射方法[J]. 计算机应用, 2011, 31(07): 1781-1784.
Xue-ru JIN Jian-dong QI Li-chen WANG Lin-zhi ZHOU. Approach of classification mapping between international patent classification and chinese library classification based on machine learning. Journal of Computer Applications, 2011, 31(07): 1781-1784.
DOAN A,DOMINGOS P,HALEVY A. Reconciling schemas of disparate data sources: A machine learning approach[C]// Proceedings of International Conference on Management of Data. New York: ACM, 2001:509-520.
[6]
DOAN A,MADHAVAN J,DOMINGOS P. Ontology matching: A machine learning approach[EB/OL].[2010-10-06].http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.8.2185&rep=rep1&type=pdf.
2011, Vol. 31 
