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» Evaluating algorithms that learn from data streams
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PAAPP
2008
76views more  PAAPP 2008»
15 years 3 months ago
Group-aware stream filtering for bandwidth-efficient data dissemination
In this paper 1 we are concerned with disseminating high-volume data streams to many simultaneous applications over a low-bandwidth wireless mesh network. For bandwidth efficiency...
Ming Li, David Kotz
129
Voted
BTW
2009
Springer
166views Database» more  BTW 2009»
15 years 10 months ago
TinTO: A Tool for View-Based Analysis of Stock Market Data Streams
: TinTO is an experimental system aiming at demonstrating the usefulness and feasibility of incrementally evaluated SQL queries for analyzing a wide spectrum of data streams. As ap...
Andreas Behrend, Christian Dorau, Rainer Manthey
CGF
2008
100views more  CGF 2008»
15 years 4 months ago
Density Displays for Data Stream Monitoring
In many business applications, large data workloads such as sales figures or process performance measures need to be monitored in real-time. The data analysts want to catch proble...
Ming C. Hao, Daniel A. Keim, Umeshwar Dayal, Danie...
DAMON
2008
Springer
15 years 5 months ago
CAM conscious integrated answering of frequent elements and top-k queries over data streams
Frequent elements and top-k queries constitute an important class of queries for data stream analysis applications. Certain applications require answers for both frequent elements...
Sudipto Das, Divyakant Agrawal, Amr El Abbadi
SODA
2008
ACM
110views Algorithms» more  SODA 2008»
15 years 5 months ago
Why simple hash functions work: exploiting the entropy in a data stream
Hashing is fundamental to many algorithms and data structures widely used in practice. For theoretical analysis of hashing, there have been two main approaches. First, one can ass...
Michael Mitzenmacher, Salil P. Vadhan