Abstract
Previous researches on multidimensional indexes typically have used synthetic data sets distributed uniformly or normally over multidimensional space for performance evaluation. These kinds of data sets hardly reflect the characteristics of multimedia database applications. In this paper, we discuss issues on generating high dimensional data and query sets for resolving the problem. We first identify the requirements of the data and query sets for fair performance evaluation of multidimensional indexes, and then propose HDDQ_Gen (High-Dimensional Data and Query Generator) that satisfies such requirements. HDDQ_Gen has the following features: (1) clustered distribution, (2) various object distribution in each cluster, (3) various cluster distribution, (4) various correlations among different dimensions, and (5) query distribution depending on data distribution. Using these features, users are able to control the distribution characteristics of data and query sets appropriate for their target applications.
This research was supported by the MIC, Korea, under the ITRC support program supervised by the IITA (IITA-2005-C1090-0502-0009).
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Kim, SW., Yoon, SH., Lee, SC., Lee, J., Shin, M. (2007). Generating High Dimensional Data and Query Sets. In: van Leeuwen, J., Italiano, G.F., van der Hoek, W., Meinel, C., Sack, H., Plášil, F. (eds) SOFSEM 2007: Theory and Practice of Computer Science. SOFSEM 2007. Lecture Notes in Computer Science, vol 4362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69507-3_30
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DOI: https://doi.org/10.1007/978-3-540-69507-3_30
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