Information integration
Cohesive synthesis of information
From Wikipedia, the free encyclopedia
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, a related term, involves the combination of information into a new set of information in order to reduce 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.[citation needed] Other methods rely on causal estimates of the outcomes based on a model of the sources.[2]
See also
Further reading
- M. E. Liggins; D. L. Hall; J. Llinas (2008). Multisensor Data Fusion: Theory and Practice (Second ed.). CRC Press. ISBN 978-1-4200-5308-1.
- D. L. Hall; S. A. H. McMullen (2004). Mathematical Techniques in Multisensor Data Fusion. Artech House. ISBN 978-1-58053-335-5.
- Information Fusion in Data Mining. Springer. 2003. ISBN 3-540-00676-1.
- H. B. Mitchell (2007). Multi-sensor Data Fusion: An Introduction. Berlin: Springer-Verlag. ISBN 978-3-540-71463-7.
- S. Das (2008). High-Level Data Fusion. Norwood, Massachusetts: Artech House. ISBN 978-1-59693-281-4.
- E. P. Blasch; E. Bosse; D. A. Lambert (2012). High-Level Information Fusion Management and System Design. Norwood, Massachusetts: Artech House. ISBN 978-1-60807-151-7.
- L. Snidaro; J. Garcia-Herrero; J. Llinas; et al. (2016). Context-Enhanced Information Fusion: Boosting Real-World Performance with Domain Knowledge. Springer-Verlag. ISBN 978-3-319-28969-4.