Dealing with Data Streams: Complex Event Processing vs. Data Stream Mining
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-58811-3_1
Reference22 articles.
1. Aggarwal, C.C.: Data Mining. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-14142-8
2. Aggarwal, C.C., Han, J., Wang, J., Yu, P.S.: A framework for clustering evolving data streams. In: Proceedings of the 29th International Conference on Very Large Data Bases-Volume 29, pp. 81–92. VLDB Endowment (2003)
3. Babcock, B., Babu, S., Datar, M., Motwani, R., Widom, J.: Models and issues in data stream systems. In: Proceedings of the Twenty-First ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pp. 1–16. ACM (2002)
4. Bruns, R., Dunkel, J.: Event-Driven Architecture: Softwarearchitektur fürereignisgesteuerte Geschäftsprozesse. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-02439-9
5. Bruns, R., Dunkel, J.: Complex Event Processing. Springer, Wiesbaden (2015). https://doi.org/10.1007/978-3-658-09899-5
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