Sampling cube: A framework for statistical OLAP over sampling data

Proceedings of the ACM SIGMOD International Conference on Management of Data

Volumn , Issue , 2008, Pages 779-790

  Li, Xiaolei ^a   Han, Jiawei ^a   Yin, Zhijun ^a   Lee, Jae Gil ^a   Sun, Yizhou ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

Algorithms; Design; Experimentation

Indexed keywords

CLUSTERING ALGORITHMS; DATA STORAGE EQUIPMENT; SAMPLING;

CONFIDENCE INTERVALS; DATA COLLECTIONS; EXPERIMENTATION; HIGHDIMENSIONAL DATUMS; MULTIDIMENSIONAL QUERIES; MULTIDIMENSIONAL SPACES; MULTIPLE ATTRIBUTES; ONLINE-ANALYTICAL PROCESSING; OVER SAMPLINGS; QUERY RESULTS; SAMPLING DATUMS; STORAGE REQUIREMENTS; TELEVISION SHOWS; UNITED STATES;

POPULATION STATISTICS;

EID: 57149135463     PISSN: 07308078     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1376616.1376695     Document Type: Conference Paper

References (22)

1. C. C. Aggarwal and P. S. Yu. Outlier detection for high dimensional data. In SIGMOD'01.
2. O. Benjelloun, A. D. Sarma, A. Y. Halevy, and J. Widom. Uldbs: Databases with uncertainty and lineage. In VLDB'06.
3. K. Beyer and R. Ramakrishnan. Bottom-up computation of sparse and iceberg cubes. In SIGMOD'99.
4. D. Burdick, P. Deshpande, T. S. Jayram, R. Ramakrishnan. and S. Vaithyanathan. Olap over uncertain and imprecise data. In VLDB'05.
5. D. Burdick, A. Doan, R. Ramakrishnan, and S. Vaithyanathan. Olap over imprecise data with domain constraints. In VXDS'07.
6. Surajit Chaudhuri, Kris Ganjam, Venkatesh Ganti, and Rajeev Motwani. Robust and efficient fuzzy match for online data cleaning. In SIGMOD '03.
7. Bee-Chung Chen, Lei Chen, Yi Lin, and Raghu Ramakrishnan. Prediction cubes. In VLDB'05.
8. P.-A. Chirita, C. S. Firan, and W. Nejdl. Personalized query expansion for the web. In SIGIR'07.
9. H. Cui, J.-R. Wen, J.-Y. Nie, and W.-Y. Ma. Query expansion by mining user logs. IEEE TKDE'03.
10. J. Gray, A. Bosworth, A. Layman, and H. Pirahesh. Data cube: A relational operator generalizing group-by, cross-tab and sub-totals. In ICDE'96.
11. I. Guyon and A. Elisseeff. An introduction to variable and feature selection. In Journal of Machine Learning Research, 2003.
12. V. Harinarayan, A. Rajaraman, and J. D. Ullman. Implementing data cubes efficiently. In SIGMOD '96.
13. W. L. Hays. Statistics. CBS College Publishing, New York, NY, 1981.
14. L. V. S. Lakshmanan, J. Pei, and J. Han. Quotient cube: How to summarize the semantics of a data cube. In VLDB'02.
15. L. V. S. Lakshmanan, J. Pei, and Y. Zhao. QC-Trees: An efficient summary structure for semantic OLAP. In SIGMOD'O3.
16. X. Li, J. Han, and H. Gonzalez. High-dimensional OLAP: A minimal cubing approach. In VLDB'04
17. T. M. Mitchell. Machine Learning. McGraw Hill, 1997.
18. L. Parsons, E. Haque, and H. Liu. Subspace clustering for high dimensional data: A review. SIGKDD Explorations, 2004.
19. V. Raman and J. M. Hellerstein. Potter's wheel: An interactive data cleaning system. In VLDB'01.
20. Y. Sismanis and N. Roussopoulos. The complexity of fully materialized coalesced cubes. In VLDB'04
21. I. H. Witten and E. Frank. Data Mining: Practical Machine Learning Tools and Techniques, Second Edition. Morgan Kaufmann, 2005.
22. D. Xin, J. Han, X. Li, and B. W. Wall. Star-cubing: Computing iceberg cubes by top-down and bottom-up integration. In VLDB'03.