Abstract
The access to relevant information is one of the determining factors which directly influences on decision-making processes. Huge amounts of data have been accumulated by entities from large variety of sources in many different formats. Due to large amounts of information and continuous processes of generation of new parts, it is necessary to ensure the most effective way of information or data extraction and analysis. The Web of Data provides great opportunities for ontology-based services. The combination of ontology-based approaches and Big Data may help in solving some problems related to extraction of meaningful information from various sources. This paper presents the selected ontology-based approaches to Big Data analytics as well as a proposal of a procedure for ontology-based knowledge discovery.
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Konys, A. (2017). Ontology-Based Approaches to Big Data Analytics. In: Kobayashi, Sy., Piegat, A., Pejaś, J., El Fray, I., Kacprzyk, J. (eds) Hard and Soft Computing for Artificial Intelligence, Multimedia and Security. ACS 2016. Advances in Intelligent Systems and Computing, vol 534. Springer, Cham. https://doi.org/10.1007/978-3-319-48429-7_32
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DOI: https://doi.org/10.1007/978-3-319-48429-7_32
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