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A Solution of data Inconsistencies in data Integration——Designed for Pervasive Computing Environment

Journal of Computer Science & Technology 2010年第3期25卷 499-508页

作者：王欣黄林鹏章义徐小辉陈俊清 Department of Computer Science and Engineering Shanghai Jiao Tong University

New challenges including how to share information on heterogeneous devices appear in data-intensive pervasive computing environments. data integration is a practical approach to these applications. Dealing with inconsistencies is one of the important problems in data integration. In this paper we motivate the problem of data inconsistency solution for data integration in pervasive environments. We define data qualit~ criteria and expense quality criteria for data sources to solve data inconsistency. In our solution, firstly, data sources needing high expense to obtain data from them are discarded by using expense quality criteria and utility function. Since it is difficult to obtain the actual quality of data sources in pervasive computing environment, we introduce fuzzy multi-attribute group decision making approach to selecting the appropriate data sources. The experimental results show that our solution has ideal effectiveness.

关键词： pervasive computing data integration data inconsistency group decision making history credibility

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Integrate inconsistent and heterogeneous data based on user feedback

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International Journal of Intelligent Computing and Cybernetics 2015年第2期8卷 187-203页

作者： Lihua Lu Hengzhen Zhang Xiao-Zhi Gao School of Computer Science Fudan UniversityShanghaiP.R.China College of Mathematics and Information Science Zhengzhou University of Light IndustryHenanP.R.China College of Information Engineering Shanghai Maritime UniversityShanghaiP.R.China Department of Electrical Engineering and Automation School of Electrical EngineeringAalto UniversityAaltoFinland

Purpose–data integration is to combine data residing at different sources and to provide the users with a unified interface of these *** important issue on data integration is the existence of conflicts among the different data *** sources may conflict with each other at data level,which is defined as data *** purpose of this paper is to aim at this problem and propose a solution for data inconsistency in data ***/methodology/approach–A relational data model extended with data source quality criteria is first *** based on the proposed data model,a data inconsistency solution strategy is *** accomplish the strategy,fuzzy multi-attribute decision-making(MADM)approach based on data source quality criteria is applied to obtain the ***,users feedbacks strategies are proposed to optimize the result of fuzzy MADM approach as the final data inconsistent ***–To evaluate the proposed method,the data obtained from the sensors are *** experiments are designed and performed to explain the effectiveness of the proposed *** results substantiate that the solution has a better performance than the other methods on correctness,time cost and stability *** implications–Since the inconsistent data collected from the sensors are pervasive,the proposed method can solve this problem and correct the wrong choice to some ***/value–In this paper,for the first time the authors study the effect of users feedbacks on integration results aiming at the inconsistent data.

关键词： Decision making data fusion data inconsistency data integration User feedback

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