Multi-Relational learning for recommendation of matches between semantic structures

Authors:
Andrzej Szwabe;Pawel Misiorek;Przemyslaw Walkowiak
Affiliations:
Institute of Control and Information Engineering, Poznan University of Technology, Poznan, Poland;Institute of Control and Information Engineering, Poznan University of Technology, Poznan, Poland;Institute of Control and Information Engineering, Poznan University of Technology, Poznan, Poland
Venue:
KES'12 Proceedings of the 16th international conference on Knowledge Engineering, Machine Learning and Lattice Computing with Applications
Year:
2012

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Abstract

The paper presents the Tensor-based Reflective Relational Learning System (TRRLS) as a tensor-based approach to automatic recommendation of matches between nodes of semantic structures. The system may be seen as realizing a probabilistic inference with regard to the relation representing the …semantic equivalence' of ontology classes. Despite the fact that TRRLS is based on the new idea of algebraic modeling of multi-relational data, it provides results that are comparable to those achieved by the leading solutions of the Ontology Alignment Evaluation Initiative (OAEI) contest realizing the task of matching concepts of Anatomy track ontologies on the basis of partially known expert matches.