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KDD
2003
ACM
194views Data Mining» more  KDD 2003»
15 years 10 months ago
Finding recent frequent itemsets adaptively over online data streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Joong Hyuk Chang, Won Suk Lee
CF
2010
ACM
15 years 29 days ago
Towards chip-on-chip neuroscience: fast mining of neuronal spike streams using graphics hardware
Computational neuroscience is being revolutionized with the advent of multi-electrode arrays that provide real-time, dynamic perspectives into brain function. Mining neuronal spik...
Yong Cao, Debprakash Patnaik, Sean P. Ponce, Jerem...
GIS
2007
ACM
15 years 10 months ago
TerraStream: from elevation data to watershed hierarchies
We consider the problem of extracting a river network and a watershed hierarchy from a terrain given as a set of irregularly spaced points. We describe TerraStream, a "pipeli...
Andrew Danner, Thomas Mølhave, Ke Yi, Panka...
COCOON
2005
Springer
15 years 3 months ago
Finding Longest Increasing and Common Subsequences in Streaming Data
In this paper, we present algorithms and lower bounds for the Longest Increasing Subsequence (LIS) and Longest Common Subsequence (LCS) problems in the data streaming model. For t...
David Liben-Nowell, Erik Vee, An Zhu
100
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STOC
2007
ACM
142views Algorithms» more  STOC 2007»
15 years 10 months ago
Lower bounds for randomized read/write stream algorithms
Motivated by the capabilities of modern storage architectures, we consider the following generalization of the data stream model where the algorithm has sequential access to multi...
Paul Beame, T. S. Jayram, Atri Rudra