Reducing inconsistency is the key problem to improve data quality during data integration. In this paper,we first present a weighted algorithm of similarity coefficient which is superior to traditional algorithms if t...Reducing inconsistency is the key problem to improve data quality during data integration. In this paper,we first present a weighted algorithm of similarity coefficient which is superior to traditional algorithms if the sourcedata have multiple characteristic items ,all of which have to be taken into account ,especially during the complex infor-mation integration. Secondly,we apply it to the experiment of telecommunication customers integrating ,the results ofdata clustering show it has high feasibility and precision performance.展开更多
文摘Reducing inconsistency is the key problem to improve data quality during data integration. In this paper,we first present a weighted algorithm of similarity coefficient which is superior to traditional algorithms if the sourcedata have multiple characteristic items ,all of which have to be taken into account ,especially during the complex infor-mation integration. Secondly,we apply it to the experiment of telecommunication customers integrating ,the results ofdata clustering show it has high feasibility and precision performance.
