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Lee, Pei-Ju (2015) EFFICIENT INFORMATION INTEGRATION SYSTEM FOR TEMPORAL AND SPATIAL DATA. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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In this dissertation, I develop a novel inconsistency detection and data fusion method for data integration systems. Inconsistent data may lead to incorrect query results and induce unexplainable outcomes. I propose an inconsistency detection method to find out which data items (e.g., temporal or spatial report) have the higher potential to cause data conflicts as well as to estimate a reasonable consistent reported value. My approach is based on representing overlapping data reports as a characteristic linear system. The characteristic linear system can be used to estimate consistent reported values within overlapping time and space intervals. I explore applicability of the proposed approach in different domains. In particular, I perform temporal data fusion with time-overlapping reports using a historical database. I also experiment with spatial data fusion involving space-overlapping reports using simulation of sensor data sets of robots performing search and rescue task. Finally, I apply the proposed approach to combine temporal and spatial fusion and demonstrate that such multidimensional fusion improves inconsistency detection and target value estimation.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Lee, Pei-Jupel30@pitt.eduPEL30
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairZadorozhny, Vladimirviz@pitt.eduVIZ
Committee MemberHirtle, Stephen C.shirtle@sis.pitt.eduHIRTLE
Committee MemberDruzdzel, Marek J.marek@sis.pitt.eduDRUZDZEL
Committee MemberMunro, Paulpmunro@sis.pitt.eduPWM
Committee MemberGrant ,
Date: 7 May 2015
Date Type: Publication
Defense Date: 17 March 2015
Approval Date: 7 May 2015
Submission Date: 5 May 2015
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 139
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Data fusion, Information integration, Temporal and spatial data fusion, Linear system.
Date Deposited: 07 May 2015 15:37
Last Modified: 15 Nov 2016 14:28


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