NDLI: Index for fast retrieval of uncertain spatial point data

Content Provider	ACM Digital Library
Author	Hariharan, Ramaswamy Ma, Yiming Mehrotra, Sharad Kalashnikov, Dmitri V.
Abstract	Location information gathered from a variety of sources in the form of sensor data, video streams, human observations, and so on, is often imprecise and uncertain and needs to be represented approximately. To represent such uncertain location information, the use of a probabilistic model that captures the imprecise location as a probability density function (pdf) has been recently proposed. The pdfs can be arbitrarily complex depending on the type of application and the source of imprecision. Hence, efficiently representing, storing and querying pdfs is a very challenging task. While the current state of the art indexing approaches treat the representation and storage of pdfs as a black box, in this paper, we take the challenge of representing and storing any complex pdf in an efficient way. We further develop techniques to index such pdfs to support the efficient processing of location queries. Our extensive experiments demonstrate that our indexing techniques significantly outperform the best existing solutions.
Starting Page	195
Ending Page	202
Page Count	8
File Format	PDF
ISBN	1595935290
DOI	10.1145/1183471.1183504
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2006-11-10
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	U-grid Probability Uncertainty indexing Spatial database
Content Type	Text
Resource Type	Article

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Index for fast retrieval of uncertain spatial point data