A Novel Multi-classifier Integrated Model for Chinese Noun Sense Disambiguation

作     者：Jianyong Duan Yi Hu Weilin Wu Hui Liu Ruzhan Lu 

作者机构：Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai 200030 China 

出 版 物：《通讯和计算机（中英文版）》 (Journal of Communication and Computer)

年 卷 期：2006年第3卷第5期

页      面：8-13页

学科分类：08[工学] 0835[工学-软件工程] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：语言程序 中国 自然语言处理 计算机语言 

摘      要：We propose a Multi-classifier Compatible Computational Model (MCCM) for Chinese noun sense disambiguation in this paper. In natural language processing, many problems can be viewed as classification in nature. However, different classifiers cannot be efficiently integrated by a general standard. Quantification rule is introduced for flexible integration of statistical and rule-based classifiers. Rules are traced into the corpus for acquiring their quantification information. The other contribution is Projected Performance Evaluation Matrix (P-PEM). Classification performance is improved because it contains more accurate classification information for every classifier. Many faint classifiers boost a powerful MCCM model. Finally the experiment shows its advantages.