Data fusion
From Wikipedia, the free encyclopedia
Data fusion, is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences, which will be more efficient than if they were achieved by means of a single source.
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[edit] See also
- Artificial intelligence
- Bayesian network
- CRISP-DM
- Data analysis
- Data farming
- Data mining
- Descriptive statistics
- Fuzzy logic
- Hypothesis testing
- k-nearest neighbor algorithm
- Machine learning
- Pattern recognition
- Predictive analytics
- Preprocessing
- Statistics
[edit] Application areas
- Business intelligence
- Business performance management
- Discovery science
- Intelligent transport systems
- Loyalty card
- Cheminformatics
- Bioinformatics
- Intelligence services
[edit] References
[edit] General References
[edit] Books
- David L. Hall, Sonya A. H. McMullen, Mathematical Techniques in Multisensor Data Fusion (2004), ISBN 1580533353 (Bookpool.com)
- Springer, Information Fusion in Data Mining (2003), ISBN 3540006761 (Bookpool.com)
- H. B. Mitchell, Multi-sensor Data Fusion – An Introduction (2007) Springer-Verlag, Berlin, ISBN 9783540714637
[edit] External links
Look up data fusion in Wiktionary, the free dictionary.
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