Clustering relational data

A large class of clustering problems can be formulated as an optimizational problem in which the best clustering is searched among all feasible clustering according to a selected criterion function. This clustering approach can be applied to a variety of very interesting clustering problems, as it i...

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Veröffentlicht in:ITI 2008 : proceedings of the ITI 2008 30th International Conference on Information Technology Interfaces S. 13 - 18
1. Verfasser: Ferligoj, A.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Zagreb IEEE 01.06.2008
University Computing Centre
Schlagworte:
agglomerative approach
Applied sciences
blockmodeling
clustering problem
Computer science; control theory; systems
Exact sciences and technology
Information technology
Integrated circuits
optimazation
relational constraint
relocation approach
Software
Software engineering
Cluster analysis
Program specification
Relational database
Classification
ISBN:9789537138127, 9537138127
ISSN:1330-1012
Online-Zugang:Volltext
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Zusammenfassung:A large class of clustering problems can be formulated as an optimizational problem in which the best clustering is searched among all feasible clustering according to a selected criterion function. This clustering approach can be applied to a variety of very interesting clustering problems, as it is possible to adapt it to a concrete clustering problem by an appropriate specification of the criterion function and/or by the definition of the set of feasible clusterings. Both, the blockmodeling problem (clustering of the relational data) and the clustering with relational constraint problem (clustering of the attribute and relational data) can be very successfully treated by this approach. It also opens many new developments in these areas.
ISBN:9789537138127
9537138127
ISSN:1330-1012
DOI:10.1109/ITI.2008.4588378