Abstract
Recently, data generation rates are getting higher than ever before. Plenty of different sources like smartphones, social networking services and the Internet of Things (IoT) are continuously producing massive amounts of data. Due to limited resources, it is no longer feasible to persistently store all that data which leads to massive data streams. In order to meet the requirements of modern businesses, techniques have been developed to deal with these massive data streams. These include complex event processing (CEP) and data stream mining, which are covered in this article. Along with the development of these techniques, many terms and semantic overloads have occurred, making it difficult to clearly distinguish techniques for processing massive data streams. In this article, CEP and data stream mining are distinguished and compared to clarify terms and semantic overloads.
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Irina Astrova’s work was supported by the Estonian Ministry of Education and Research institutional research grant IUT33-13.
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Lange, M., Koschel, A., Astrova, I. (2020). Dealing with Data Streams: Complex Event Processing vs. Data Stream Mining. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12252. Springer, Cham. https://doi.org/10.1007/978-3-030-58811-3_1
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