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Indexed by:会议论文

Date of Publication:2007-01-01

Included Journals:CPCI-S

Page Number:232-237

Key Words:named entity recognition; fuzzy support vector machine; hybrid model

Abstract: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.