Abstract
Preference queries on data streams have been proved very useful for many application areas. Despite of the existence of research studies dedicated to this issue, they lack to support the use of an important implicit information of data streams, the temporal preferences. In this paper we define new operators and an algorithm for the efficient evaluation of temporal conditional preference queries on data streams. We also demonstrate how the proposed operators can be translated to the Continuous Query Language (CQL). The experiments performed show that our proposed operators have considerably superior performance when compared to the equivalent operations in CQL.
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Acknowledgments
The authors thanks the Research Agencies CNPq, CAPES and FAPEMIG for supporting this work.
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Ribeiro, M.R., Barioni, M.C.N., de Amo, S., Roncancio, C., Labbé, C. (2017). Temporal Conditional Preference Queries on Streams. In: Benslimane, D., Damiani, E., Grosky, W., Hameurlain, A., Sheth, A., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2017. Lecture Notes in Computer Science(), vol 10438. Springer, Cham. https://doi.org/10.1007/978-3-319-64468-4_11
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DOI: https://doi.org/10.1007/978-3-319-64468-4_11
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