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» Approximate Frequency Counts over Data Streams
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SSDBM
2008
IEEE
111views Database» more  SSDBM 2008»
15 years 4 months ago
iJoin: Importance-Aware Join Approximation over Data Streams
We consider approximate join processing over data streams when memory limitations cause incoming tuples to overflow the available space, precluding exact processing. Selective evi...
Dhananjay Kulkarni, Chinya V. Ravishankar
JIIS
2007
150views more  JIIS 2007»
14 years 9 months ago
Towards a new approach for mining frequent itemsets on data stream
Mining frequent patterns on streaming data is a new challenging problem for the data mining community since data arrives sequentially in the form of continuous rapid streams. In t...
Chedy Raïssi, Pascal Poncelet, Maguelonne Tei...
CIDR
2003
163views Algorithms» more  CIDR 2003»
14 years 11 months ago
Query Processing, Approximation, and Resource Management in a Data Stream Management System
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system for executing continuous queries over multiple continuous data streams. The ST...
Rajeev Motwani, Jennifer Widom, Arvind Arasu, Bria...
ICDE
2008
IEEE
192views Database» more  ICDE 2008»
15 years 11 months ago
Verifying and Mining Frequent Patterns from Large Windows over Data Streams
Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
Barzan Mozafari, Hetal Thakkar, Carlo Zaniolo
PODS
2009
ACM
100views Database» more  PODS 2009»
15 years 10 months ago
Space-optimal heavy hitters with strong error bounds
The problem of finding heavy hitters and approximating the frequencies of items is at the heart of many problems in data stream analysis. It has been observed that several propose...
Radu Berinde, Graham Cormode, Piotr Indyk, Martin ...