Use of ontological knowledge in machine learning methods for intelligent analysis of Big Data

• Дата: 2019
• Автор: Rogushina, J.V.
• Формат: Стаття
• Мова: Ukrainian
• Опубліковано: PROBLEMS IN PROGRAMMING 2019
• Теми: machine learning; Big Data; ontology; UDC 004,853; 004.55
• Онлайн доступ: https://pp.isofts.kiev.ua/index.php/ojs1/article/view/336
• Назва журналу: Problems in programming

The paper discusses problems related to the processing of Big Data in order to acquire implicit knowledge from them. Machine  learning (ML) methods oriented on these tasks can be combined with elements of the Semantic Web technologies and Artificial Intelligence (AI), which deals with intelligent behavior, learning and adaptation in computational systems. We analyse challenges and opportunities background knowledge using to improve ML results, the role of ontologies and other   resources of domain knowledge. Domain knowledge could improve the quality of ML results by using reasoning techniques to select learning models and prepare the training and test data. We propose some examples demonstrated the  use of ontologies and semantic Wiki markup for improving the efficiency of machine learning are considered deal with functional posibilities of the portal version of the Great Ukrainian Encyclopedia. Ontological model of this informational resource is considered as a domain knowledge base. Groupping  of examples is based on high-level ontological classes, and semantic properties and their relations are used for construction of space of attributes.Problems in programming 2018; 4: 69-81