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1 Journal of Theoretical and Applied Computer Science

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Case Studies on Big Data

Globa L., Svetsynska I., Luntovskyy A.

Journal of Theoretical and Applied Computer Science

2016

Vol. 10, nr 2

41--52

The main idea of the Data Mining (DM) is nowadays as follows: overcoming of the Big Data problematics is possible under use of "data compression" via their transformation into (fuzzy) knowledge. The "heavy-weighting approaches" involving precise analytical techniques and expensive specialized software are used for this aim. On the other hand, there is the opportunity to solve the Big Data problem under use of some "light-weighting approaches" based on agility: freeware, multipurpose techniques, minimal challenges on the personnel training and competencies! The paper examines the techniques and case studies on the both topics. The "heavy-weighting approaches" (ontologies, knowledge bases, fuzzy logic and fuzzy knowledge bases) are compared to light-weighting one. The existing reference solutions are discussed.