摘要
海量中文信息处理是大数据处理的一个分支,而利用大数据技术进行中文信息处理一定离不开中文分词,所以中文分词技术是大数据中文信息处理的基础性技术.中文分词技术自本世纪以来,一直在性能与精确度两个方向在推进;在性能方面主要以改进分词扫瞄算法,改进词库存储技术与查询方式来提高性能.在精确度上主要是对未登录词与歧义词的甄别与处理方法进行改进.本文摒弃了通过词库索引查询的思想,提出一种基于字符树的词库存储结构.它的分词速度是普通折半法的35倍,占用内存只是它的1/5.它将为大数据技术在处理中文信息时在性能上推进了一大步.
Massive Chinese information processing is a branch of big data processing, and the use of big data technology for Chinese information processing must be inseparable from Chinese word segmentation, so Chinese word segmentation technology is the basic technology of big data Chinese information processing. Chinese word segmentation technology has been advancing in performance and accuracy since this century. In terms of performance, it mainly improves the segmentation scanning algorithm, the word bank storage technology, and query method to improve the performance. In terms of accuracy, it is mainly to improve the processing method of unregistered words and ambiguous words. This paper gives up the idea of searching by lexicon index and proposes a lexicon storage structure based on character tree. Its segmenting speed is 35 times faster than the normal half method, occupying only 1/5 of its memory. It will be a big step forward in the performance of big data technology in processing Chinese information.
作者
杨光豹
杨丰赫
郑慧锦
YANG Guang-Bao;YANG Feng-He;ZHENG Hui-Jin(Qingtian College, Zhejiang Radio & TV University, Qingtian 323900, China;School of Cyber Science and Engineering, Southeast University, Nanjing 211189, China;Zhejiang Qingtian Vocational and Technical School, Qingtian 323900, China)
出处
《计算机系统应用》
2019年第8期262-267,共6页
Computer Systems & Applications
关键词
字符树
中文分词
散列法
折半法
时间复杂度
character tree
Chinese word segmentation
hash
binary query
time complexity