Release Time:2019-03-12  Hits:

Indexed by: Conference Paper

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.