Title :
Co-reference Resolution in Vietnamese Documents Based on Support Vector Machines
Author :
Le, Duc-Trong ; Tran, Mai-Vu ; Nguyen, Tri-Thanh ; Ha, Quang-Thuy
Author_Institution :
KTLab, Coll. of Technol. Vietnam Nat. Univ., Hanoi, Vietnam
Abstract :
Co-reference resolution task still poses many challenges due to the complexity of the Vietnamese language, and the lack of standard Vietnamese linguistic resources. Based on the mention-pair model of Rahman and Ng. (2009) and the characteristics of Vietnamese, this paper proposes a model using support vector machines (SVM) to solve the co-reference in Vietnamese documents. The corpus used in experiments to evaluate the proposed model was constructed from 200 articles in cultural and social categories from vnexpress.net newspaper website. The results of the initial experiments of the proposed model achieved 76.51% accuracy in comparison with that of the baseline model of 73.79% with similar features.
Keywords :
natural language processing; support vector machines; Vietnamese documents; Vietnamese language; Vietnamese linguistic resources; co-reference resolution; support vector machines; Accuracy; Buildings; Educational institutions; Semantics; Support vector machine classification; Training; Co-reference resolution; Vietnamese co-reference; support vector machines;
Conference_Titel :
Asian Language Processing (IALP), 2011 International Conference on
Conference_Location :
Penang
Print_ISBN :
978-1-4577-1733-8
DOI :
10.1109/IALP.2011.63