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XIN WANG, LIN-PENG HUANG, XIAO-HUI XU, YI ZHANG AND JUN-QING CHEN
Department of Computer Science and Engineering
Shanghai Jiao Tong University
Shanghai, 200240 P.R. China
Data integration is a problem of combining data residing at different sources and
providing the user with a unified view of these data. An important issue in data integration
is the possibility of conflicts among the different data sources. Data sources may
conflict with each other at data value level which is defined as data inconsistency. So in
this paper, a solution for data inconsistency in data integration is proposed. An approximate
object-oriented data model extended with data source quality criteria is defined. On
the basis of our data model, we provide a data inconsistency solution strategy. To accomplish
our strategy, fuzzy multi-attribute decision making approach based on data
source quality criteria is applied to select the "best" data source's data as the data inconsistency
solution. A set of experiments is designed and performed to evaluate the effectiveness
of our strategy and algorithm. The experimental results indicate that our solution
performs ideally.
Received March 10, 2009; revised May 26 & July 16, 2009; accepted September 26, 2009.
Communicated by Suh-Yin Lee.
* The work was supported by the National Natural Science Foundation of China under Grant No. 60970010 and
973 Program of China No. 2009CB320705.