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电力大数据:2019,22(10):-
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一种基于最小距离编辑法的模糊地址识别模型
金鹏1, 杨菁2, 王宗伟1, 刘鲲鹏1, 卜晓阳1
(1.国网客服中心;2.国家电网公司客户服务中心)
A Fuzzy Address Recognition Model Based on Minimum Distance Editing
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投稿时间:2019-06-20    修订日期:2019-08-02
中文摘要: 由于受到客户方言及语言习惯因素影响,加之呼叫中心客服坐席手工记录客户地址的形式不统一,难以实现精确筛选细化到小区、村庄级别的相近地址,支撑定位客户反映的频繁停电等问题。该文提出了一种地址模糊匹配模型,根据地址信息的字符和拼音形式,利用最小编辑距离算法和支持向量机分类相结合的新型模糊识别方法,能够实现对相近地址的精准研判。仿真结果表明,该方法可以克服谐音字对地址识别的影响,具有计算速度快且识别能力强的优势,能够支撑筛选频繁停电地址等场景应用。
Abstract:Due to the influence of the customers dialect,and the form of customers’addresses that operators of power electrical call center manually record are diverse,it is difficult to accurately find the similar addresses in village level and locate frequent blackouts. In this paper, a fuzzy address matching model is proposed. Based on the character and pinyin forms of address information, similar addresses can be effectively located by the minimum edit distance algorithm and Support Vector Machine(SVM) classifier. The simulation results show that the method can overcome the influence of homophonic words with fast calculation and high reliability. Scenario applications such as locating frequent outage addresses can be supported by the method.
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