On-line analytical processing (OLAP) requires e cient processing of complex decision support queries over very large databases. It is well accepted that pre-computed data cubes ca...
David Wai-Lok Cheung, Bo Zhou, Ben Kao, Hongjun Lu...
Approximating the joint data distribution of a multi-dimensional data set through a compact and accurate histogram synopsis is a fundamental problem arising in numerous practical ...
Amol Deshpande, Minos N. Garofalakis, Rajeev Rasto...
Approximate query processing has emerged as a costeffective approach for dealing with the huge data volumes and stringent response-time requirements of today's decision-suppo...
Kaushik Chakrabarti, Minos N. Garofalakis, Rajeev ...
We propose an novel method of computing and storing DataCubes. Our idea is to use Bayesian Networks, which can generate approximate counts for any query combination of attribute v...
In this paper we propose a new wavelet transform applicable to functions defined on graphs, high dimensional data and networks. The proposed method generalizes the Haar-like transf...