计算机应用与软件Issue(2)：25-29,5.DOI:10.3969/j.issn.1000-386x.2016.02.006
基于 DBSCAN 聚类算法的多模式匹配
MULTI-SCHEMA MATCHING BASED ON DBSCAN CLUSTERING ALGORITHM
摘要
Abstract
Schema matching has wide application in many database correlated fields,such as data integration,data space and data warehouse.Matching task between only two attributes is what the traditional matching techniques study,but the matching task between multiple attributes is ignored.With respect to this problem,we proposed a multi-schema integration technique in this paper,which is based on DBSCAN (density-based spatial clustering of applications with noise)clustering algorithm.The proposed approach focus on the discovery of semantic correspondence among multiple attributes,which is a more complex issue relative to discovering the pairwise-attribute correspondence.Our main study idea is to deem every attribute as a point in the vector space,and then to partition these attributes into different sets by clustering technique.The attributes within same cluster have similar semantics.Meanwhile,we utilised the information sources of Web structure to improve the quality of schema matching results.At last,we performed extensive experimental research to verify the approach,and the experimental results showed that our approach was effective and had good performance.关键词
模式匹配/语义对应关系/结构化信息/聚类技术Key words
Schema matching/Semantic correspondence/Structured information/Clustering technique分类
信息技术与安全科学引用本文复制引用
丁国辉,许莹南,郭军宏..基于 DBSCAN 聚类算法的多模式匹配[J].计算机应用与软件,2016,(2):25-29,5.基金项目
国家自然科学基金项目（61303016）；辽宁省教育厅一般项目（L2012045）。 （）
