Abstract
Systems supporting situation awareness typically deal with
a vast stream of information about a large number of real-world objects
anchored in time and space provided by multiple sources. These
sources are often characterized by frequent updates, heterogeneous formats
and most crucial, identical, incomplete and often even contradictory
information. In this respect, duplicate detection methods are of
paramount importance allowing to explore whether or not information
having, e. g., different origins or different observation times concern one
and the same real-world object. Although many such duplicate detection
methods have been proposed in literature - each of them having different
origins, pursuing different goals and often, by nature, being heavily
domain-specific - the unique characteristics of situation awareness and
their implications on the method's applicability were not the focus up
to now. This paper examines existing duplicate detection methods appearing
to be suitable in the area of situation awareness and identifies
their strengths and shortcomings. As a prerequisite, based on a motivating
case study in the domain of road traffic management, an evaluation
framework is suggested, which categorizes the major requirements on
duplicate detection methods with regard to situation awareness.
Original language | English |
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Title of host publication | Proceedings of the 8th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2009), Vilamoura, Algarve-Portugal |
Pages | 1050-1068 |
Number of pages | 18 |
Publication status | Published - 2009 |
Fields of science
- 101004 Biomathematics
- 101027 Dynamical systems
- 101028 Mathematical modelling
- 101029 Mathematical statistics
- 101014 Numerical mathematics
- 101015 Operations research
- 101016 Optimisation
- 101017 Game theory
- 101018 Statistics
- 101019 Stochastics
- 101024 Probability theory
- 101026 Time series analysis
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102004 Bioinformatics
- 102013 Human-computer interaction
- 102018 Artificial neural networks
- 102019 Machine learning
- 103029 Statistical physics
- 106005 Bioinformatics
- 106007 Biostatistics
- 202017 Embedded systems
- 202035 Robotics
- 202036 Sensor systems
- 202037 Signal processing
- 305901 Computer-aided diagnosis and therapy
- 305905 Medical informatics
- 305907 Medical statistics
- 102032 Computational intelligence
- 102033 Data mining
- 101031 Approximation theory
- 102002 Augmented reality
- 102006 Computer supported cooperative work (CSCW)
- 102015 Information systems
- 102021 Pervasive computing
- 102025 Distributed systems
- 102027 Web engineering
- 202038 Telecommunications