TitleA study on relation extraction of historical figures based on bibliographic description
AuthorsXu, Jingyi
Zhang, Shuai
Li, Duo
Yu, Shiwen
AffiliationInstitute of Computational Linguistics, Peking University, Beijing, China
Department of Chinese Language and Literature, Peking University, Beijing, China
Issue Date2011
Citation2011 International Conference on Computer Science and Service System, CSSS 2011.Nanjing, China.
AbstractFigure relation extraction is an important and hard field in information extraction. In this paper, aiming to improve the performance for relation extraction of historical figures, we propose a novel method based on bibliographic description. In the proposed method, by analyzing the species and co-occurrence relation of responsibility in a bibliographic record, we combine diverse person responsibility, person name and time as features, whose values are the quantity of the species clustering concerned, to build a Decision Tree model. Accordingly, relation extraction of historical figures is performed through the model. It is experimentally shown that on average, 83.3% and 83.0% in precision and recall rate are achieved respectively without more linguistic knowledge and complex classifiers. ? 2011 IEEE.
Appears in Collections:中国语言文学系

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