TY - GEN
T1 - CubeExplorer
T2 - 2002 ACM SIGMOD International Conference on Management of Data, SIGMOD 2002
AU - Han, Jiawei
AU - Wang, Jianyong
AU - Dong, Guozhu
AU - Pei, Jian
AU - Wang, Ke
N1 - Funding Information:
* The work was supportedin part by NSERC and NCE of Canadaa nd the Univ. of Illinois at Urbana-Champaign.
Funding Information:
The work was supported in part by NSERC and NCE of Canada and the Univ. of Illinois at Urbana-Champaign.
Publisher Copyright:
© 2002 ACM.
PY - 2002/6/3
Y1 - 2002/6/3
N2 - 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 [2], cube-based feature extraction, and gradient analysis [1], 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.
AB - 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 [2], cube-based feature extraction, and gradient analysis [1], 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.
UR - http://www.scopus.com/inward/record.url?scp=85134316573&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134316573&partnerID=8YFLogxK
U2 - 10.1145/564691.564781
DO - 10.1145/564691.564781
M3 - Conference contribution
AN - SCOPUS:85134316573
T3 - Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, SIGMOD 2002
SP - 626
BT - Proceedings of the 2002 ACM SIGMOD International Conference on Management of Data, SIGMOD 2002
PB - Association for Computing Machinery, Inc
Y2 - 3 June 2002 through 6 June 2002
ER -