An approximate Lp-difference algorithm for massive data streams?

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1770, Issue , 2000, Pages 193-204

  Fong, Jessica H ^a   Strauss, Martin J ^b  

^a PRINCETON UNIVERSITY   (United States)

^b AT AND T LABS RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; ERRORS; METADATA;

DATA SET; DATA-SOURCE; DIFFERENCE ALGORITHMS; FUNCTION VALUES; MASSIVE DATA SETS; MASSIVE DATA STREAMS; RELATIVE ERRORS;

DATA STREAMS;

EID: 84944053774     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-46541-3_16     Document Type: Conference Paper

References (11)

1. N. Alon, P. Gibbons, Y. Matias, and M. Szegedy. Tracking Join and Self-Join Sizes in Limited Storage. In Proc. of the 18'th Symp. on Principles of Database Systems, ACM Press, New York, pages 10-20, 1999.
2. N. Alon, Y. Matias, and M. Szegedy. The space complexity of approximating the frequency moments. In Proc. of 28'th STOC, pages 20-29, 1996. To appear in Journal of Computing and System Sciences.
3. N. Alon and J. Spencer. The Probabilistic Method. Wiley, 1992.
4. A. Broder, M. Charikar, A. Frieze, and M. Mitzenmacher. Min-wise independent permutations. In Proc. of the 30'th STOC, pages 327-336, 1998.
5. Cisco NetFlow, 1998. http://www.cisco.com/warp/public/732/netflow/.
6. J. Feigenbaum. Locally random reductions in interactive complexity theory. DI- MACS Series in Discrete Mathematics and Theoretical Computer Science, vol. 13, pages 73-98. American Mathematical Society, Providence, 1993.
7. J. Feigenbaum, S. Kannan, M. Strauss, and M. Viswanathan. An Approximate L1- Difference Algorithm for Massive Data Streams. To appear in Proc. of the 40'th IEEE Symposium on Foundataions of Computer Science, 1999.
8. J. Feigenbaum and M. Strauss. An Information-Theoretic Treatment of Random- Self-Reducibility. Proc. of the 14'th Symposium on Theoretical Aspects of Computer Science, pages 523-534. Lecture Notes in Computer Science, vol. 1200, Springer- Verlag, New York, 1997.
9. P. Gibbons and Y. Matias. Synopsis Data Structures for Massive Data Sets. To appear in Proc. 1998 DIMACS Workshop on External Memory Algorithms. DI- MACS Series in Discrete Mathematics and Theoretical Computer Science, American Mathematical Society, Providence. Abstract in Proc. Tenth Symposium on Discrete Algorithms, ACM Press, New York and Society for Industrial and Applied Mathematics, Philadelphia, pages S909-910, 1999.
10. M. Rauch Henzinger, P. Raghavan, and S. Rajagopalan. Computing on data streams. Technical Report 1998-011, Digital Equipment Corporation Systems Re- search Center, May 1998.
11. E. Kushilevitz, R. Ostrovsky, Y. Rabani. Efficient Search for Approximate Nearest Neighbor in High Dimensional Spaces. Proc. of The 30's ACM Symposium on Theory of Computing, ACM Press, New York, pages 514-523.