Abstract: We present the large-scale linguistic ontology OENT aimed for the using in NLP for the solving of information retrieval tasks such as categorization and query expansion in the domain of natural science and technology. OENT is based on three approaches - traditions of librarian information retrieval thesauri, formal ontologies, WordNet-like resources.Also we describe several additional rules for concepts, text entries and relations. OENT includes 50 thousands concepts, more than 150 thousands text entries, 200 thousands direct relations and more than two millions inherited relations.

Abstract:

The paper discusses the use of machine learning mechanisms, natural language analysis and intellectual search in the field of jurisprudence. The main expected results are the methodology for applying text-based analytics and semantic natural language processing (NLP) algorithms in knowledge management cases in different types of legal practice. The obtained results can be applied in the field of education and knowledge management in a wider context, since the study lies at the union of jurisprudence, mathematical and computer linguistics.

We describe a prototype of a multi-agent system of intellectual analysis of legal texts that is capable of identifying general dependencies on the existing database of legal documents, providing legal cases with similar topics, recommending the most likely outcomes of judicial review.