计算机科学 ›› 2017, Vol. 44 ›› Issue (9): 266-271.doi: 10.11896/j.issn.1002-137X.2017.09.050
许普乐,王杨,黄亚坤,黄少芬,赵传信,陈付龙
XU Pu-le, WANG Yang, HUANG Ya-kun, HUANG Shao-fen, ZHAO Chuan-xin and CHEN Fu-long
摘要： 传统的中文地名地址匹配技术难以处理大数据环境下海量、多样和异构的智慧城市地理信息空间中的中文地名地址快速匹配问题。提出了一种Spark计算平台下基于中文地名地址要素的匹配框架及应用智能决策的匹配算法(An Intelligent Decision Matching Algorithm,AIDMA)。首先,从中文地名地址中富含的语义性和中文字符串、数字与字母之间的自然分隔性两个方面进行地址要素解析,构建了融合多距离信息的贝叶斯推理网络,从而提出了基于多准则评判的中文地名地址匹配决策方法。然后,利用芜湖市514967条脱敏后的燃气开户中文地名地址信息库与1770979条网格化社区中的中文地名地址信息库(包含网格化地址的地理空间信息)进行实验与分析。实验结果表明,在处理大规模中文地名地址信息时,相比于传统的中文地名地址匹配方法,该方法能够有效提高单条中文地名地址的匹配效率,同时在匹配度与精确度两个指标上匹配结果更加均衡。
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