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» Mining data streams with periodically changing distributions
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IPPS
2006
IEEE
14 years 2 months ago
Supporting self-adaptation in streaming data mining applications
There are many application classes where the users are flexible with respect to the output quality. At the same time, there are other constraints, such as the need for real-time ...
Liang Chen, Gagan Agrawal
CN
2006
163views more  CN 2006»
13 years 8 months ago
A framework for mining evolving trends in Web data streams using dynamic learning and retrospective validation
The expanding and dynamic nature of the Web poses enormous challenges to most data mining techniques that try to extract patterns from Web data, such as Web usage and Web content....
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
ICDM
2010
IEEE
189views Data Mining» more  ICDM 2010»
13 years 6 months ago
S4: Distributed Stream Computing Platform
Abstract--S4 is a general-purpose, distributed, scalable, partially fault-tolerant, pluggable platform that allows programmers to easily develop applications for processing continu...
Leonardo Neumeyer, Bruce Robbins, Anish Nair, Anan...
EPIA
2003
Springer
14 years 1 months ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
WSDM
2009
ACM
136views Data Mining» more  WSDM 2009»
14 years 3 months ago
Mining common topics from multiple asynchronous text streams
Text streams are becoming more and more ubiquitous, in the forms of news feeds, weblog archives and so on, which result in a large volume of data. An effective way to explore the...
Xiang Wang 0002, Kai Zhang, Xiaoming Jin, Dou Shen