| 基于统计的分词系统字典模型研究 |
| |
| 引用本文： | 李小龙.基于统计的分词系统字典模型研究[J].湖北工业大学学报,2010,25(5):71-73,79. |
| |
| 作者姓名： | 李小龙 |
| |
| 作者单位： | 湖北工业大学计算机学院,湖北,武汉,430068 |
| |
| 摘 要： | 在传统基于统计的中文分词系统基础上加以总结和改进,通过向量空间建立字典模型,改进了倒排字典设计,引入了改进的字典自我学习的功能,优化了字典排序的算法,提高了查询的速度.
|
| 关 键 词： | 中文分词系统 向量空间 倒排字典 算法 |
On the System Dictionary of Sub-word Based on Statistical Model |
| |
| LI Xiao-long.On the System Dictionary of Sub-word Based on Statistical Model[J].Journal of Hubei University of Technology,2010,25(5):71-73,79. |
| |
| Authors: | LI Xiao-long |
| |
| Affiliation: | LI Xiao-long(School of Computer,Hubei University of Technology,Wuhan 430068,China) |
| |
| Abstract: | The segmentation of Chinese character is the foundation of Chinese information processing system.This paper sums up and improves Chinese character segmentation system based on the traditional statistics.A dictionary model is established to improve inverted dictionary design through the vector space.A improved dictionary self-learning function is introduced,the dictionary sorting algorithm is optimized,and the query speed is improved. |
| |
| Keywords: | Chinese character segmentation system vector space the inverted dictionary the algorithm |
| 本文献已被 维普 万方数据 等数据库收录！ |
|
