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CubeExplorer: Online exploration of data cubes

Publication ,  Conference
Han, J; Wang, J; Dong, G; Pei, J; Wang, K
Published in: Proceedings of the ACM SIGMOD International Conference on Management of Data
September 17, 2002

Data cube enables fast online analysis of large data repositories, which is attractive in many applications. Although there are several kinds of available cube-based OLAP products, users may still encounter challenges on effectiveness and efficiency in the exploration of large data cubes due to the huge computation space as well as the huge observation space in a data cube. CubeExplorer is an integrated environment for online exploration of data cubes. It integrates our newly developed techniques on iceberg cube computation, cube-based feature extraction, and gradient analysis, and makes cube exploration effective and efficient. In this demo, we will show the features of CubeExplorer, especially its power and flexibility at exploring and mining of large databases.

Duke Scholars

Published In

Proceedings of the ACM SIGMOD International Conference on Management of Data

ISSN

0730-8078

Publication Date

September 17, 2002

Start / End Page

626
 

Citation

APA
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MLA
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Han, J., Wang, J., Dong, G., Pei, J., & Wang, K. (2002). CubeExplorer: Online exploration of data cubes. In Proceedings of the ACM SIGMOD International Conference on Management of Data (p. 626).
Han, J., J. Wang, G. Dong, J. Pei, and K. Wang. “CubeExplorer: Online exploration of data cubes.” In Proceedings of the ACM SIGMOD International Conference on Management of Data, 626, 2002.
Han J, Wang J, Dong G, Pei J, Wang K. CubeExplorer: Online exploration of data cubes. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. 2002. p. 626.
Han, J., et al. “CubeExplorer: Online exploration of data cubes.” Proceedings of the ACM SIGMOD International Conference on Management of Data, 2002, p. 626.
Han J, Wang J, Dong G, Pei J, Wang K. CubeExplorer: Online exploration of data cubes. Proceedings of the ACM SIGMOD International Conference on Management of Data. 2002. p. 626.

Published In

Proceedings of the ACM SIGMOD International Conference on Management of Data

ISSN

0730-8078

Publication Date

September 17, 2002

Start / End Page

626