Personal Name Recognition Based on Categorized Linguistic Knowledge

This paper proposes an integrated approach for personal name recognition (PNR) in Chinese by utilizing both statistical language models and categorized linguistic knowledge. Various formulas are proposed for calculating personal name credibility and context credibility for different types of persona...

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Bibliographic Details
Published in2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Vol. 3; pp. 311 - 315
Main Authors Qu, Weiguang, Tang, Xuri, Li, Bin
Format Conference Proceeding
LanguageEnglish
Published Washington, DC, USA IEEE Computer Society 09.12.2008
IEEE
SeriesACM Conferences
Subjects
Applied computing > Document management and text processing
Character recognition
Computing methodologies > Artificial intelligence > Knowledge representation and reasoning
Computing methodologies > Artificial intelligence > Natural language processing
Credibility
Discourse
Europe
Intelligent agent
Knowledge database
Large-scale systems
Mathematics
Natural languages
Personal Name Recognition
Probability
Statistical analysis
Statistics
Theory of computation > Logic
Discourse
Credibility
Personal Name Recognition
Knowledge database
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Summary:This paper proposes an integrated approach for personal name recognition (PNR) in Chinese by utilizing both statistical language models and categorized linguistic knowledge. Various formulas are proposed for calculating personal name credibility and context credibility for different types of personal names. Experiment is conducted on large-scale corpus to evaluate the approach and the F-1 scores has reached 98.85% and 92.73% respectively in close and open test.
ISBN:9780769534961
0769534961
DOI:10.1109/WIIAT.2008.155