摘要
为了解决大量专利数据的存储和翻译问题,设计了一种基于Hadoop的专利翻译系统。针对数据存储该系统采用了HDFS和HBase相结合的混合式存储结构,对于翻译过程则采用Hadoop并行翻译模型-MapReduce。通过实验证明,相比于传统的翻译方法该系统具有更好的数据存储和翻译性能。
In order to tackle the problem of storing and translation of massive patent literatures,a patent literatures translation system based on Hadoop is proposed in this paper. The paper presents a hybrid storage structure which combines HDFS and HBase,and a parallel translation model-MapReduce. The experimental results show that the proposed machine translation system has better translation performance than the conventional machine translation approach.
出处
《信息技术》
2015年第10期30-33,37,共5页
Information Technology
基金
国家重点基础研究发展计划(973计划)资助项目(2013CB329303)
