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Title: Recognition and extraction of honorifics in chinese diachronic corpora
Authors: Xiong, D
Xu, J
Lu, Q 
Lo, F
Keywords: Chinese diachronic corpora
Machine learning algorithm
Issue Date: 2014
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2014, v. 8922, p. 305-316 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: Honorifics in this paper refer to names of official positions and titles of nobility or honor. They can be found in various written records in different periods and have great historical significance. This paper introduces a machine learning system to recognize the honorifics in diachronic corpora. A tagged corpus of four classic novels written in the Ming and Qing dynasties is used to train the system. The system is then used to automatically recognize and extract the honorifics in pre-Qin classics, Tang-dynasty poems, and modern Chinese news. Experimental results show that the system can achieve relatively good results in recognizing the honorifics in the pre-Qin classics and Tang-dynasty poems. This work is an attempt to improve the performance of automatic recognition of honorifics in diachronic corpora. The system can be a helpful tool in the studies on the evolution of honorifics throughout Chinese history.
Description: 15th Workshop on Chinese Lexical Semantics, CLSW 2014, Macao, 9-12 June 2014
ISBN: 9783319143309
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-319-14331-6_31
Appears in Collections:Conference Paper

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