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» Sketching probabilistic data streams
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ICDE
2008
IEEE
135views Database» more  ICDE 2008»
14 years 8 months ago
Online Filtering, Smoothing and Probabilistic Modeling of Streaming data
In this paper, we address the problem of extending a relational database system to facilitate efficient real-time application of dynamic probabilistic models to streaming data. he ...
Bhargav Kanagal, Amol Deshpande
SIGMOD
2002
ACM
198views Database» more  SIGMOD 2002»
14 years 7 months ago
Processing complex aggregate queries over data streams
Recent years have witnessed an increasing interest in designing algorithms for querying and analyzing streaming data (i.e., data that is seen only once in a fixed order) with only...
Alin Dobra, Minos N. Garofalakis, Johannes Gehrke,...
VLDB
2002
ACM
137views Database» more  VLDB 2002»
13 years 7 months ago
Comparing Data Streams Using Hamming Norms (How to Zero In)
Massive data streams are now fundamental to many data processing applications. For example, Internet routers produce large scale diagnostic data streams. Such streams are rarely s...
Graham Cormode, Mayur Datar, Piotr Indyk, S. Muthu...
SIGMOD
2006
ACM
116views Database» more  SIGMOD 2006»
14 years 7 months ago
Approximately detecting duplicates for streaming data using stable bloom filters
Traditional duplicate elimination techniques are not applicable to many data stream applications. In general, precisely eliminating duplicates in an unbounded data stream is not f...
Fan Deng, Davood Rafiei
NIPS
2008
13 years 9 months ago
One sketch for all: Theory and Application of Conditional Random Sampling
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
Ping Li, Kenneth Ward Church, Trevor Hastie