NDLI: Indexing uncertain spatio-temporal data

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Indexing uncertain spatio-temporal data

Content Provider	ACM Digital Library
Author	Renz, Matthias Mamoulis, Nikos Züfle, Andreas Emrich, Tobias Kriegel, Hans-Peter
Abstract	The advances in sensing and telecommunication technologies allow the collection and management of vast amounts of spatio-temporal data combining location and time information.Due to physical and resource limitations of data collection devices (e.g., RFID readers, GPS receivers and other sensors) data are typically collected only at discrete points of time. In-between these discrete time instances, the positions of tracked moving objects are uncertain. In this work, we propose novel approximation techniques in order to probabilistically bound the uncertain movement of objects; these techniques allow for efficient and effective filtering during query evaluation using an hierarchical index structure.To the best of our knowledge, this is the first approach that supports query evaluation on very large uncertain spatio-temporal databases, adhering to possible worlds semantics. We experimentally show that it accelerates the existing, scan-based approach by orders of magnitude.
Starting Page	395
Ending Page	404
Page Count	10
File Format	PDF
ISBN	9781450311564
DOI	10.1145/2396761.2396813
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-10-29
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Uncertain trajectory Uncertain spatio-temporal data Indexing
Content Type	Text
Resource Type	Article

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