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

Abstract: 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.