分布式策略与CRFs相结合识别汉语组块  

A Distributed Strategy for CRFs Based Chinese Text Chunking

作　　者：黄德根[1] 于静[1] 

机构地区：[1]大连理工大学计算机科学与工程系,辽宁大连116024

出　　处：《中文信息学报》2009年第1期16-22,共7页Journal of Chinese Information Processing

基　　金：国家863高技术研究发展计划资助项目(2006AA012140);国家自然科学基金资助项目(60673039)

摘　　要：该文提出了一种基于CRFs的分布式策略及错误驱动的方法识别汉语组块。该方法首先将11种类型的汉语组块进行分组,结合CRFs构建不同的组块识别模型来识别组块;之后利用基于CRFs的错误驱动技术自动对分组组块进行二次识别;最后依据各分组F值大小顺序处理类型冲突。实验结果表明,基于CRFs的分布式策略及错误驱动方法识别汉语组块是有效的,系统开放式测试的精确率、召回率、F值分别达到94.90%、91.00%和92.91%,好于单独的CRFs方法、分布式策略方法及其他组合方法。This paper proposes a distributed strategy for Chinese text chunking on the basis Conditional Random Fields（CRFs） and Error-driven technique. First eleven types of Chinese chunks are divided into different groups to build CRFs model respectively. Then, the error-driven technique is applied over CRFs chunking results for further modification. Finally, a method is described to deal with the conflicting chunking according to the F-measure values. The experimental results show that this approach is effective, outperforming the single CRFs-based approach, distributed method and other hybrid approaches in the open test by achieving reaches 94.90%, 91.00% ,and 92.91% in recall, precision, and F-measure respectively.

关 键 词：计算机应用 中文信息处理 组块识别 条件随机域(CRFs) 分布式策略 基于CRFs的错误驱动 浅层句法分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]