An Attribute Similarity Adjusting Algorithm Based on Functional Dependency
The accuracy of attribute similarity is one of the important factors affecting the precision of entity resolution (ER).To improve the accuracy of attribute similarity,the relation between attribute similarity and functional dependency (FD) was analyzed and the principles for attribute similarity adjusting were suggested.The FD based methods for similarity partition,similarity transitively adjusting and cost computing of similarity adjusting were proposed.An algorithm for attribute similarity adjusting with FD (SAWFD) was put forward to improve the accuracy of attribute similarity.The experiment results show that the algorithm can better distinguish matching and unmatching records,and get higher scores of recall,precision and F1 measure.
NETL
NSTL
万方数据
维普
