Information integration
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Information integration (II) is the merging of information from heterogeneous sources with differing conceptual, contextual and typographical representations. It is used in data mining and consolidation of data from unstructured or semi-structured resources. Typically, information integration refers to textual representations of knowledge but is sometimes applied to rich-media content. Information fusion, which is a related term, involves the combination of information into a new set of information towards reducing redundancy and uncertainty.[1]
Examples of technologies available to integrate information include deduplication, and string metrics which allow the detection of similar text in different data sources by fuzzy matching. A host of methods for these research areas are available such as those presented in the International Society of Information Fusion. Other methods rely on causal estimates of the outcomes based on a model of the sources.[2]
See also
- Data fusion (is a subset of Information integration)
- Sensor fusion
- Data integration
- Image fusion
- Synesthesia
Books
- <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>M. E. Liggins; D. L. Hall; J. Llinas (2008). Theory and Practice (Multisensor Data Fusion) (Second ed.). CRC. ISBN 978-1-4200-5308-1.
- <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>D. L. Hall; S. A. H. McMullen (2004). Mathematical Techniques in Multisensor Data Fusion. ISBN 978-1-58053-335-5.
- Springer, Information Fusion in Data Mining (2003), <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>ISBN 3-540-00676-1
- H. B. Mitchell, Multi-sensor Data Fusion – An Introduction (2007) Springer-Verlag, Berlin, <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>ISBN 978-3-540-71463-7
- S. Das, High-Level Data Fusion (2008), Artech House Publishers, Norwood, MA, <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>ISBN 978-1-59693-281-4 and 1596932813
- E. P. Blasch, E. Bosse, and D. A. Lambert, High-Level Information Fusion Management and System Design (2012), Artech House Publishers, Norwood, MA. <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>ISBN 1608071510 | <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>ISBN 978-1608071517
- <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>L. Snidaro; J. Garcia-Herrero; J. Llinas; et al. (2016). Context-Enhanced Information Fusion: Boosting Real-World Performance with Domain Knowledge. Springer-Verlag. ISBN 978-3319289694.
References
External links
- Discriminant Correlation Analysis (DCA)
- Information Integration Using Logical View LNCS 1997.
- International Society of Information Fusion
ar:تكامل البيانات de:Informationsintegration
- ↑ <templatestyles src="Module:Citation/CS1/styles.css"></templatestyles>Haghighat, Mohammad; Abdel-Mottaleb, Mohamed; Alhalabi, Wadee (2016). "Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition". IEEE Transactions on Information Forensics and Security. 11 (9): 1984–1996. doi:10.1109/TIFS.2016.2569061. S2CID 15624506.
- ↑ P.K. Davis, D. Manheim, W.L. Perry, J. Hollywood (2015). In Proceedings of the 2015 Winter Simulation Conference (WSC '15). IEEE Press, Piscataway, NJ, USA, 2586-2597.
