A rule and super function-based machine translation system for Chinese-Japanese causative sentences

被引：0

作者：

Mi, Liying ^{[1
]}

Luo, Xin ^{[1
]}

Ren, Fuji ^{[1
,2
]}

Kuroiwa, Shingo ^{[1
]}

机构：

[1] Faculty of Engineering, The University of Tokushima, 2-1 Minamijosanjima, Tokushima 770-8506, Japan

[2] School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

来源：

WSEAS Transactions on Computers | 2006年 / 5卷 / 09期

关键词：

Database systems - Formal languages - Knowledge based systems - Maintainability - Quality of service;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Machine translation (MT) can be generally classified as Rule-Based Machine Translation (RBMT) or Example-Based Machine Translation (EBMT) or Statistics-Based Machine Translation (SBMT), and each has numerous problems which remain unsolved. A rule-based machine translation system is an effective way to implement a machine translation system because of its extensibility and maintainability. However, it is generally disadvantageous in processing efficiency. In this paper, we present a hybrid approach based on fixed rules and Super Functions (SF) - Based method. SF is known for its lower costs, and is applicability to common users who do not have high demand on translation quality. Our purpose is to improve the processing efficiency and the quality of machine translation. In the present research, sufficient Chinese-Japanese causative sentence patterns have been employed as a language-database for experiment, which proves the suggested method can effectively improve translation quality within the range under discussion.

引用

页码：2122 / 2129