From Meaningful Orderings in the Web of Data to Multi-level Pattern Structures

International audienceWe define a pattern structure whose objects are elements of a supporting ontology. In this framework, descriptions constitute trees, made of triples subject-predicate-object, and for which we provide a meaningful similarity operator. The specificity of the descriptions depends on a hy-perparameter corresponding to their depth. This formalism is compatible with ontologies formulated in the language of RDF and RDFS and aims to set up a framework based on pattern structures for knowledge discovery in the web of data

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

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 dominancebased 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 system

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

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 dominancebased 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 system