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Paradigmatic and Syntagmatic Relations in Information Systems over Ontological Graphs

Pancerz K.

Fundamenta Informaticae

2016

Vol. 148, nr 1/2

229--242

The main goal of the paper is to show the idea of incorporating paradigmatic and syntagmatic relations into processing data stored in information tables using rough set methods. Input data, in a tabular form, are used in many machine learning and computational intelligence methods and algorithms, among others, those based on rough set theory. Additional knowledge about semantic relations (both paradigmatic and syntagmatic) can be considered as a useful context affecting data classification or clustering.

Ant-based extraction of rules in simple decision systems over ontological graphs

Pancerz K., Lewicki A., Tadeusiewicz R.

International Journal of Applied Mathematics and Computer Science

2015

Vol. 25, no. 2

377--387

In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominance-based rough set approach (DRSA). In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems.