A Chinese Person Name Recognition System Based on Agent-based HMM Position Tagging Model

Author

Guo, Yimo ; Gao, Huanping

Author_Institution

Dept. of Comput. Sci., Tianjin Normal Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

4069

Lastpage

4072

Abstract

An agent-based HMM position tagging (AHPT) model was proposed for Chinese person name recognition. The model unified unknown word identification and person name recognition as a single tagging task. Based on context pattern, special name table and position dependent information, the model could integrate both the internal information and surrounding contextual clues for name entity recognition (NER) under the HMM. The experiment shows that the recall rate and precise rate are respectively 95.11% and 94.02%. The result indicates the application of multi-agent framework can substantially improve the performance of HMM in person name recognition

Keywords

character recognition; hidden Markov models; image recognition; multi-agent systems; natural languages; Chinese person name recognition system; agent-based HMM position tagging model; context pattern; hidden Markov model; multiagent framework; name entity recognition; position dependent information; special name table; word identification; Computer science; Context modeling; Dictionaries; Hidden Markov models; Natural languages; Pattern recognition; Robustness; Statistics; Tagging; Writing; Name Entity Recognition (NER); hidden markov model (HMM); person name recognition; position (POS) tagging;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713139

Filename

1713139