SPARQL

The article proposes a method and intelligent information system for semantic analysis and automatic classification of human movement biomechanical data in rehabilitation systems. The method is based on the integration of a formal biomechanical description of movement with biomedical ontologies, which provides multi-level data processing: signal preprocessing, spatio-temporal feature extraction, ontological knowledge representation and automatic classification of movement patterns.

The article presents the development and formalization of an algorithm for pattern matching in graph representations of textual data as a core component of syntactic-semantic transformations for ontology construction from text documents. The study aims to bridge the gap between natural language processing and formal logic by introducing a universal SPARQL-based approach for executing transf- ormation rules directly on graph database servers.