DocumentCode
2002091
Title
Adaptive Interpolation Algorithms for Temporal-Oriented Datasets
Author
Gao, Jun
Author_Institution
Dept. of Comput. Sci. & Eng., Nebraska Univ., Lincoln, NE
fYear
2006
fDate
15-17 June 2006
Firstpage
145
Lastpage
151
Abstract
Spatiotemporal datasets can be classified into two categories: temporal-oriented and spatial-oriented datasets depending on whether missing spatiotemporal values are closer to the values of its temporal or spatial neighbors. We present an adaptive spatiotemporal interpolation model that can estimate the missing values in both categories of spatiotemporal datasets. The key parameters of the adaptive spatiotemporal interpolation model can be adjusted based on experience
Keywords
interpolation; temporal databases; visual databases; adaptive spatiotemporal interpolation model; spatial-oriented datasets; spatiotemporal datasets; temporal-oriented datasets; Computer science; Data engineering; Data visualization; Interpolation; Nominations and elections; Pollution; Shape; Spatiotemporal phenomena; Temperature; Voting;
fLanguage
English
Publisher
ieee
Conference_Titel
Temporal Representation and Reasoning, 2006. TIME 2006. Thirteenth International Symposium on
Conference_Location
Budapest
ISSN
1530-1311
Print_ISBN
0-7695-2617-9
Type
conf
DOI
10.1109/TIME.2006.4
Filename
1635992
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