基于条件随机场的多特征未登录地址元素识别方法

An Identification Method of Unknown Address Elements Based on Conditional Random Field Considering Multiple Features

在基于地址匹配的位置服务中,分词词典和地址数据库更新不及时会导致地址切分和地址匹配准确性降低,无法实现定位或定位错误。因此,快速准确地识别未登录地址元素,扩充和更新分词词典具有重要意义。针对现有方法的不足,提出了一种基于条件随机场的多特征未登录地址元素识别方法,结合了词法特征、语义特征、字词特征、构词能力特征。根据这些特征建立条件随机场模型对未登录地址元素进行识别分析。实验结果表明,未登录地址元素识别精确率、召回率、F_(1)值分别达到了95.1%、94.9%、95.0%。

In the location service based on address matching,the accuracy of address segmentation and address matching is reduced due to the untimely update of word segmentation dictionary and address database.Therefore,it is important to quickly and accurately identify the unknown address elements and expand and update the word segmentation dictionary.Aiming at the shortcomings of the existing methods,we propose an identification method of unknown address elements based on conditional random field considering multiple features,which combines lexical features,semantic features,word features and word formation ability features.Then we establish a conditional random field model to identify and analyze the unknown address elements according to these features.The experimental results show that the identification accuracy,recall and F_(1) value of unknown address elements reach 95.1%,94.9% and 95%,respectively.