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Propositionalisation and Aggregates
A.J. Knobbe,
M. de Haas,
and A. Siebes.
In Proceedings of the 5th European Conference on Principles of Data Mining
and Knowledge Discovery, pages 277--288. Springer-Verlag, September
2001. More behind this link.
Abstract
The fact that data is scattered over many tables causes many problems in the
practice of data mining. To deal with this problem, one either constructs a
single table by hand, or one uses a Multi-Relational Data Mining algorithm.
In this paper, we propose a different approach in which the single table is
constructed automatically using aggregate functions, which repeatedly
summarise information from different tables over associations in the
datamodel. Following the construction of the single table, we apply
traditional data mining algorithms. Next to an in-depth discussion of our
approach, the paper presents results of experiments on three well-known data
sets.
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