Berko, Andrii2019-10-312019-10-312019-04-182019-04-18Berko A. Knowledge-based Big Data Cleanup method / Andrii Berko // Computational Linguistics and Intelligent Systems. — Lviv : Lviv Politechnic Publishing House, 2019. — Vol 2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18-19, 2019. — P. 14–21. — (Paper presentations).2523-4013https://ena.lpnu.ua/handle/ntb/45491Unlike traditional databases, Big Data stored as NoSQL data resources. Therefore such resources are not ready for efficient use in its original form in most cases. It is due to the availability of various kinds of data anomalies. Most of these anomalies are such as data duplication, ambiguity, inaccuracy, contradiction, absence, the incompleteness of data, etc. To eliminate such incorrectness, data source special cleanup procedures are needed. Data cleanup process requires additional information about the composition, content, meaning, and function of this Big Data resource. Using the special knowledge base can provide a resolving of such problem.14-21enBig DataOntologyKnowledge BaseData CleanupArticle© 2019 for the individual papers by the papers’ authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.8Berko A. Knowledge-based Big Data Cleanup method / Andrii Berko // Computational Linguistics and Intelligent Systems. — Lviv Politechnic Publishing House, 2019. — Vol 2 : Proceedings of the 3nd International conference, COLINS 2019. Workshop, Kharkiv, Ukraine, April 18-19, 2019. — P. 14–21. — (Paper presentations).