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» Mining time-changing data streams
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KDD
2007
ACM
182views Data Mining» more  KDD 2007»
14 years 8 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
GECCO
2004
Springer
102views Optimization» more  GECCO 2004»
14 years 1 months ago
Dynamic and Scalable Evolutionary Data Mining: An Approach Based on a Self-Adaptive Multiple Expression Mechanism
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving da...
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
ICDE
2007
IEEE
167views Database» more  ICDE 2007»
14 years 1 months ago
Load Shedding for Window Joins on Multiple Data Streams
We consider the problem of semantic load shedding for continuous queries containing window joins on multiple data streams and propose a robust approach that is effective with the ...
Yan-Nei Law, Carlo Zaniolo
JCST
2008
121views more  JCST 2008»
13 years 7 months ago
Clustering Text Data Streams
Abstract Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organiza...
Yubao Liu, Jiarong Cai, Jian Yin, Ada Wai-Chee Fu
ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
13 years 11 months ago
Sequential Change Detection on Data Streams
Model-based declarative queries are becoming an attractive paradigm for interacting with many data stream applications. This has led to the development of techniques to accurately...
S. Muthukrishnan, Eric van den Berg, Yihua Wu