Abstract
Most recent applications such as sensor networks generate continuous data streams. Additional constraints are faced for efficient query processing of such data streams that have uncertain nature and require fast and timely processing. Traditional query processing techniques of static data process the whole data without partitioning them, which is not applicable to data streams. Applying data clustering is demanded as a preprocessing step of data streams. Thus, in this paper, we propose the Incomplete High dimensional Data streams Query processing (IHDQ) algorithm for efficiently answering data streams queries. Obtained results reveal the efficiency of clustering and query processing of the proposed IHDQ compared to the alternative state-of-the-art approaches.
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Najib, F.M., Ismail, R.M., Badr, N.L., Gharib, T.F. (2021). An Efficient Approach for Query Processing of Incomplete High Dimensional Data Streams. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_57
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DOI: https://doi.org/10.1007/978-3-030-69717-4_57
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