A method of recognizing the root of an improved dependency tree for the Chinese patent literature

Author

Yun Zhu ; Yaohong Jin

Author_Institution

Inst. of Chinese Inf. Process., Beijing Normal Univ., Beijing, China

Volume

03

fYear

2012

fDate

Oct. 30 2012-Nov. 1 2012

Firstpage

1517

Lastpage

1523

Abstract

Compared with ordinary text, patent text in Chinese often has more complex sentence structure and more ambiguity of multiple verbs, which brings more difficulties in patent machine translation. To deal with these problems, this paper presents an improved dependency tree and a method to recognize the root of this tree for Chinese-English patent machine translation. Based on the theory of Hierarchical Network of Concepts (the HNC theory), some semantic features are used in the recognition. Experiments show that the precision of the recognition is close to 85%.

Keywords

language translation; natural language processing; patents; Chinese patent literature; Chinese-English patent machine translation; HNC theory; dependency tree; hierarchical network of concepts; patent text; root recognition method; sentence structure; Grammar; Magnetic heads; Patents; Semantics; Statistical analysis; Syntactics; Technological innovation; dependency tree; patent literature; predicate chunk; root; semantic features;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-1855-6

Type

conf

DOI

10.1109/CCIS.2012.6664638

Filename

6664638