Abstract
Storing, querying, and analyzing spatio-temporal data are becoming increasingly important, as the availability of volumes of spatio-temporal data increases. One important class of spatio-temporal analysis is computing spatio-temporal queries similarity. In this paper, we focus on assessing the similarity between Spatio-Temporal OLAP queries in term of their GeoMDX queries. However, the problem of measuring Spatio-Temporal OLAP queries similarity has not been studied so far.Therefore, we aim at filling this gap by proposing a novel similarity measure. The proposed measure can be used either in developing query recommendation, personalization systems or speeding-up query evolution. It takes into account the temporal similarity and the basic components of spatial similarity assessment relationships.
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Layouni, O., Akaichi, J. (2016). New Similarity Measure for Spatio-Temporal OLAP Queries. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_26
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DOI: https://doi.org/10.1007/978-3-319-34099-9_26
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