论文类型：会议论文
收录刊物：CPCI-S
页面范围：232-237
关键字：named entity recognition; fuzzy support vector machine; hybrid model
摘要：Chinese Named Entity Recognition, as a task of providing important semantic information, is a critical first step in information extraction and question answering systems. This paper proposes a hybrid method for NE recognition which combines HMM model and FSVM model. At the bottom level of the system, the person name and simple NEs are recognized by the character-based SVM. At the top level of the system, the complicated NEs are recognized by the word-based SVM. The character-based and word-based SVM are integrated. Adoption of fuzzy SVM helps reduce the impact of noise samples and abnormal data, and improve accuracy of the system.