About one approach to automatic creation of formal queries to ontological knowledge bases

• Дата: 2024
• Автори: Palagin, O.V., Petrenko, M.G., Litvin, A.A., Boyko, M.O.
• Формат: Стаття
• Мова: English
• Опубліковано: PROBLEMS IN PROGRAMMING 2024
• Теми: Semantic Web technology; ontological knowledge base; OWL ontology; SPARQL and Cypher languages; Neo4J graph database; UDC 004.318
• Онлайн доступ: https://pp.isofts.kiev.ua/index.php/ojs1/article/view/653
• Назва журналу: Problems in programming

The article develops an approach that includes the analysis of short natural language messages in Ukrainian and the automatic generation of queries in SPARQL and Cypher based on them. The Apache Jena Fuseki server is used as a SPARQL query processing tool, and the Neo4J graph database is used as a data warehouse or ontological knowledge base. The latter is the most common open source database, highperformance and well-scalable, i.e., capable of working with large amounts of data. In addition, approaches to building formal queries based on natural language queries for Cypher are little known and require further development. The approach is based on the fact that a user's natural language query is subjected to a series of sequential checks. Their results determine the set of semantic types expressed in the phrase (natural language query) and the corresponding concepts that define them. The result of these checks is a set of four values – the codes of the check results, as well as the subjects and predicates, if present. This information is enough to select a set of basic templates for formal queries. Based on the results of such basic checks, the main basic templates for generating the final request are created. The proposed approach has a basic query template aimed at obtaining information of a certain type in a given form, as well as additional modifier templates that optionally construct query strings in the corresponding blocks of the main query by introducing additional conditions. The article describes the process of automatic generation of SPARQL queries to a contextual ontology using the example of a knowledge base of medical articles from peer-reviewed open access journals. The peculiarity of the approach is that the formal query is automatically built from blocks of templates (main and auxiliary), which are customizable in accordance with certain semantic categories present in the analyzed text and the entities that specify them.Prombles in programming 2024; 2-3: 326-333