Abstract
Understanding the structure of relationships between objects in a given database is one of the most important problems in the field of data mining. The structure can be defined for a set of single objects (clustering) or a set of groups of objects (network mapping). We propose a method for discovering relationships between individuals (single or groups) that is based on what we call the empirical topology, a system-theoretic measure of functional proximity. To illustrate the suitability and efficiency of the method, we apply it to an astronomical data base.
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Dashti, H.T., Kloc, M.E., Simas, T., Ribeiro, R.A., Assadi, A.H. (2010). Introduction of Empirical Topology in Construction of Relationship Networks of Informative Objects. In: Camarinha-Matos, L.M., Pereira, P., Ribeiro, L. (eds) Emerging Trends in Technological Innovation. DoCEIS 2010. IFIP Advances in Information and Communication Technology, vol 314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11628-5_4
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DOI: https://doi.org/10.1007/978-3-642-11628-5_4
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