Title :
A new Chinese-English machine translation method based on rule for claims sentence of Chinese patent
Author :
Xiong, Wen ; Jin, Yaohong
Author_Institution :
CPIC-BNU Joint Lab. of Machine Translation, Beijing Normal Univ., Beijing, China
Abstract :
Machine translation (MT) is a hot research in artificial intelligence (AI) and natural language processing (NLP), which has mainly four directions such as statistics-based, instance-based, rule-based, and interlingua-based. To improve the quality of translation for Chinese patent, the paper proposes a new MT method based on rule for the claim sentences of Chinese patent. First, it analyzes the composition of the claims, and presents a Backus-Normal-Form (BNF) expression to parse them into fixed and variable parts. Then, it translates the fixed with prepared texts and the variable using a MT system based on syntax-rule. Finally, it integrates them into a full sentence. Experiments show that the BNF expression has a coverage ratio of 94.74% for claims on a Chinese patent dataset collected manually, which indicates its availability.
Keywords :
language translation; natural language processing; patents; text analysis; Backus-Normal-Form expression; Chinese patent; Chinese-English machine translation; artificial intelligence; claims sentence rule; instance-based machine translation; interlingua-based machine translation; natural language processing; rule-based machine translation; statistics-based machine translation; syntax-rule; Computational modeling; Syntactics; artificial intelligence (AI); finite state machine (FSM); hierarchical network of concepts (HNC); machine translation (MT); natural language processing (NLP);
Conference_Titel :
Natural Language Processing andKnowledge Engineering (NLP-KE), 2011 7th International Conference on
Conference_Location :
Tokushima
Print_ISBN :
978-1-61284-729-0
DOI :
10.1109/NLPKE.2011.6138228