摘要
模式匹配是数据集成的重要步骤之一,而数据库异构、数据量大等特点是匹配的难点所在。在梳理模式匹配概念和研究现状的基础上,提出一种基于Q-Gram数据库模式匹配算法,通过对实例数据进行切分,计算域之间的相似度,得到域的语义匹配度。该算法具有线性的时间复杂度,实验显示其能给出较为精确的匹配结果。
Schema matching is one of the important steps of data integration,and the characteristics of heterogeneous of database,large amount of data are the difficulties. Based on carding the concept of schema matching and the research status,this paper puts forward a database schema matching algorithm based on Q-Gram,through the instance data shard,calculating the similarity between domains,obtaining the semantic matching degree. The algorithm has linear time complexity,the experiments show that it can give out accurate matching results.
出处
《信息技术》
2015年第8期139-142,148,共5页
Information Technology
