Towards Highly Performant Context Awareness in the Internet of Things

Author:

Werner EliasORCID

Publisher

Springer International Publishing

Reference22 articles.

1. Barros, R.S.M., Santos, S.G.T.C.: A large-scale comparison of concept drift detectors. Inf. Sci. 451, 348–370 (2018)

2. Bifet, A., Gavalda, R.: Learning from time-changing data with adaptive windowing. In: Proceedings of the 2007 SIAM International Conference on Data Mining, pp. 443–448. SIAM (2007)

3. Bifet, A., Holmes, G., Pfahringer, B., Kranen, P., Kremer, H., Jansen, T., Seidl, T.: Moa: Massive online analysis, a framework for stream classification and clustering. In: Proceedings of the First Workshop on Applications of Pattern Analysis, pp. 44–50, PMLR (2010)

4. Frenzel, J., Feldhoff, K., Jaekel, R., Mueller-Pfefferkorn, R.: Tracing of multi-threaded java applications in score-p using bytecode instrumentation. In: ARCS Workshop 2018

5. 31th International Conference on Architecture of Computing Systems, pp. 1-8, VDE (2018)

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