Estimating statistical aggregates on probabilistic data streams

Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems

Volumn , Issue , 2007, Pages 243-252

  Jayram, T S ^a   McGregor, Andrew ^b   Muthukrishnan, S ^c   Vee, Erik ^d  

^a IBM ALMADEN RESEARCH CENTER   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c GOOGLE INC   (United States)

^d YAHOO RESEARCH   (United States)

Author keywords

Frequency moments; Mean; Median; OLAP; Probabilistic streams

Indexed keywords

DATA STREAM ALGORITHMS; FREQUENCY MOMENTS; PROBABILISTIC STREAMS;

PARAMETER ESTIMATION; PROBABILISTIC LOGICS; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS; UNCERTAINTY ANALYSIS;

DATA STRUCTURES;

EID: 35448934923     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1265530.1265565     Document Type: Conference Paper

References (23)

1. N. Alon, Y. Matias, and M. Szegedy. The space complexity of approximating the frequency moments. Journal of Computer and System Sciences, 58(1):137-147, 1999.
2. B. Babcock, S. Babu, M. Datar, R. Motwani, and J. Widom. Models and issues in data stream systems. ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, pages 1-16, 2002.
3. M. Balazinska, H. Balakrishnan, and M. Stonebraker. Load management and high availability in the medusa distributed stream processing system. In ACM SIGMOD International Conference on Management of Data, pages 929-930, 2004.
4. Z. Bar-Yossef, T. Jayram, R. Kumar, D. Sivakumar, and L. Trevisan. Counting distinct elements in a data stream. In Proc. 6th International Workshop on Randomization and Approximation Techniques in Computer Science, pages 1-10, 2002.
5. T. Batu, S. Kannan, S. Khanna, and A. McGregor. Reconstructing strings from random traces. In ACM-SIAM Symposium on Discrete Algorithms, pages 910-918, 2004.
6. D. Burdick, P. Deshpande, T. S. Jayram, R. Ramakrishnan, and S. Vaithyanathan. OLAP over uncertain and imprecise data,. In International Conference on Very Large Data Bases (VLDB), pages 970-981, 2005.
7. D. Burdick, P. M. Deshpande, T. S. Jayram, R. Ramakrishnan, and S. Vaithyanathan. OLAP over uncertain and imprecise data. In International Conference on Very Large Data Bases (VLDB), pages 970-981. VLDB Endowment, 2005.
8. D. Burdick, P. M. Deshpande, T. S. Jayram, R. Ramakrishnan, and S. Vaithyanathan. Efficient allocation algorithms for OLAP over imprecise data. In International Conference on Very Large Data Bases (VLDB), pages 391-402, 2006.
9. K. L. Chang and R. Kannan. The space complexity of pass-efficient algorithms for clustering. In A CM-SIAM Symposium on Discrete Algorithms, pages 1157-1166, 2006.
10. G. Cormode and M. Garofalakis. Sketching probabilistic data streams. In ACM SIGMOD International Conference on Management of Data, 2007.
11. C. D. Cranor, T. Johnson, O. Spatscheck, and V. Shkapenyuk. Gigascope: A stream database for network applications. In ACM SIGMOD International Conference on Management of Data, pages 647-651, 2003.
12. N. N. Dalvi and D. Suciu. Efficient query evaluation on probabilistic databases. In International Conference on Very Large Data Bases (VLDB), pages 864-875, 2004.
13. J. Feigenbaum, S. Kannan, A. McGregor, S. Suri, and J. Zhang. Graph distances in the streaming model: the value of space. In ACM-SIAM Symposium on Discrete Algorithms, pages 745-754, 2005.
14. J. Feigenbaum, S. Kannan, A. McGregor, S. Suri, and J. Zhang. On graph problems in a semi-streaming model. Theoretical Computer Science, 348(2-3):207-216, 2005.
15. P. Flajolet and G. N. Martin. Probabilistic counting algorithms for data base applications. J. Comput. Syst. Sci., 31(2):182-209, 1985.
16. N. Fuhr and T. Roelleke. A probabilistic relational algebra for the integration of information retrieval and database systems. ACM Trans. Inf. Syst., 15(1):32-66, 1997.
17. M. Greenwald and S. Khanna. Space-efficient online computation of quantile summaries. In ACM SIGMOD International Conference on Management of Data, pages 58-66, 2001.
18. S. Guha and A. McGregor. Space-Efficient Sampling. In AISTATS, pages 169-176, 2007.
19. P. Indyk. Algorithms for dynamic geometric problems over data streams. In A CM Symposium on Theory of Computing, pages 373-380, 2004.
20. T. Jayram, S. Kale, and E. Vee. Efficient aggregation algorithms for probabilistic data. In ACM-SIAM Symposium on Discrete Algorithms, 2007.
21. S. Kannan and A. McGregor. More on reconstructing strings from random traces: Insertions and deletions. In IEEE International Symposium on Information Theory, pages 297-301, 2005.
22. J. I. Munro and M. Paterson. Selection and sorting with limited storage. Theor. Comput. Sci., 12:315-323, 1980.
23. S. Muthukrishnan. Data streams: Algorithms and applications. Now Publishers, 2006.