计算机工程与应用Issue(3)：117-123,7.DOI:10.3778/j.issn.1002-8331.1303-0331
基于抽样的Deep Web模式匹配框架
Deep Web schema matching frame based on sampling
摘要
Abstract
The dual correlation mining frame has a low precision when some special schemas are in the set. Inspired by bagging algorithm in machine learning, a schema matching frame based on sampling is proposed. The frame randomly sample several subsets form input schemas, then execute the DCM matcher on each subset. The frame will achieve a robust matching accuracy by synthesizing the results of each subset. Experimental results show that the precision is increased by 41.2%in average.关键词
Deep Web/模式匹配/相关性挖掘/抽样Key words
Deep Web/schema matching/dual correlation mining/sampling分类
信息技术与安全科学引用本文复制引用
袁淼,王鑫..基于抽样的Deep Web模式匹配框架[J].计算机工程与应用,2015,(3):117-123,7.基金项目
安徽省自然科学基金（No.090412051）。 （）
