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Integration Computing and Collective Intelligence

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 511))

Abstract

Integration is a process in which one of the following aspects should be realised:

  • Several objects are merged to give a new element representing them

  • Several objects create a union acting as a whole

  • Several objects are connected with each other

The first two aspects are most important and most popular [1], [3]. In general, an integration task most often refers to a set of elements (objects) with the same kind of structures, the aim of which is based on determining an element best representing the given. The kinds of structures mean for example relational, hierarchical, table etc.

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References

  1. Danilowicz, C., Nguyen, N.T.: Consensus-Based Partitions in the Space of Ordered Partitions. Pattern Recognition 21(3), 269–273 (1988)

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  2. Kern, R., Stolarczyk, T., Nguyen, N.T.: A Formal Framework for Query Decomposition and Knowledge Integration in Data Warehouse Federations. Expert Systems with Applications 40(7), 2592–2606 (2013)

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  3. Nguyen, N.T.: Advanced Methods for Inconsistent Knowledge Management. Springer, London (2008)

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  4. Nguyen, N.T.: Processing Inconsistency of Knowledge in Determining Knowledge of a Collective. Cybernetics and Systems 40(8), 670–688 (2009)

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  5. Pietranik, M., Nguyen, N.T.: A Method for Ontology Alignment Based Attribute Semantics. Cybernetics and Systems 43(4), 319–339 (2012)

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Correspondence to Ngoc Thanh Nguyen .

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© 2014 Springer International Publishing Switzerland

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Nguyen, N.T. (2014). Integration Computing and Collective Intelligence. In: Zavoral, F., Jung, J., Badica, C. (eds) Intelligent Distributed Computing VII. Studies in Computational Intelligence, vol 511. Springer, Cham. https://doi.org/10.1007/978-3-319-01571-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-01571-2_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01570-5

  • Online ISBN: 978-3-319-01571-2

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