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  1. Proceedings of the ACM SIGSPATIAL International Workshop on GeoStreaming (IWGS '10)
  2. A data stream-based evaluation framework for traffic information systems
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Microsoft framework for geospatial stream processing
Geostreaming at IBM: infosphere streams and intelligent traffic systems
The Oracle platform for real time streaming event driven architecture based solutions
Spatiotemporal summarization of traffic data streams
A data stream-based evaluation framework for traffic information systems
Framing the question: detecting and filling spatial-temporal windows
Modeling and prediction of moving region trajectories
AIMS: an SQL-based system for airspace monitoring
OpenSense: open community driven sensing of environment
Querying streaming point clusters as regions
A programming framework for integrating web-based spatiotemporal sensor data with MapReduce capabilities
Exploratory novelty identification in human activity data streams

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A data stream-based evaluation framework for traffic information systems

Content Provider ACM Digital Library
Author Quix, Christoph Schiffer, Stefan Geisler, Sandra
Abstract Traffic information systems based on mobile, in-car sensor technology are a challenge for data management systems as a huge amount of data has to be processed in real-time. Data mining methods must be adapted to cope with these challenges in handling streaming data. Although several data stream mining methods have been proposed, an evaluation of such methods in the context of traffic applications is yet missing. In this paper, we present an evaluation framework for data stream mining for traffic applications. We apply a traffic simulation software to emulate the generation of traffic data by mobile probes. The framework is evaluated in a first case study, namely queue-end detection. We show first results of the evaluation of a data stream mining method, varying multiple parameters for the traffic simulation. The goal of our work is to identify parameter settings for which the data stream mining methods produce useful results for the traffic application at hand.
Starting Page 11
Ending Page 18
Page Count 8
File Format PDF
ISBN 9781450304313
DOI 10.1145/1878500.1878505
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-11-02
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Data streams Traffic information systems Data mining
Content Type Text
Resource Type Article
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