实体分辨研究综述  

Survey on Entity Resolution

作　　者：谭明超[1] 刁兴春[1,2] 曹建军[2] 

机构地区：[1]解放军理工大学指挥信息系统学院,南京210007 [2]总参第63研究所,南京210007

出　　处：《计算机科学》2014年第4期9-12,20,共5页Computer Science

基　　金：国家自然科学基金(61070714);解放军理工大学预研基金(20110604)资助

摘　　要：实体分辨是数据集成、信息检索等领域的重要研究内容,目的是发现数据集合中的不同实体和同一实体的不同描述。将实体分辨过程划分为数据分块、记录比较和匹配决策等3个主要步骤。从记录聚集方式的角度介绍了实体分辨的数据分块方法;从字符串划分粒度的角度分析了实体分辨的记录比较方法;从记录关联方式的角度阐述了实体分辨的决策模型。最后对实体分辨研究下一步需要解决的问题进行了展望。Entity resolution （ER） is one of cemral issues of data integration and information retrieval.Its purpose is to find all real-world entities from a given dataset,and to cluster the references that refer to the same entity.ER process was partitioned into blocking step,records comparison step and matching decision step.The methods of blocking were summarized according to the way that records are clustered together,and the methods of record pair comparison are surveyed according to the size that strings are gained,and the decision models were introduced according to the way that records associate with each other.At last,the future research issues were discussed.

关 键 词：实体分辨 数据分块 相似度 决策模型 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]