Generating High Dimensional Data and Query Sets

• Published in: SOFSEM 2007: Theory and Practice of Computer Science pp. 357 - 366
• Main Authors: Kim, Sang-Wook, Yoon, Seok-Ho, Lee, Sang-Cheol, Lee, Junghoon, Shin, Miyoung
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: Geographic Information System; High Dimensional Data; Multidimensional Space; Query Point; Singular Value Decomposition
• ISBN: 3540695060; 9783540695066
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-540-69507-3_30

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.