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ISMIS
2009
Springer
13 years 12 months ago
Novelty Detection from Evolving Complex Data Streams with Time Windows
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
DIS
2010
Springer
13 years 4 months ago
Sentiment Knowledge Discovery in Twitter Streaming Data
Micro-blogs are a challenging new source of information for data mining techniques. Twitter is a micro-blogging service built to discover what is happening at any moment in time, a...
Albert Bifet, Eibe Frank
SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
13 years 6 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
JCP
2006
111views more  JCP 2006»
13 years 5 months ago
Mining Developing Trends of Dynamic Spatiotemporal Data Streams
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
Yu Meng, Margaret H. Dunham
SIGMOD
2005
ACM
162views Database» more  SIGMOD 2005»
14 years 5 months ago
Fast and Approximate Stream Mining of Quantiles and Frequencies Using Graphics Processors
We present algorithms for fast quantile and frequency estimation in large data streams using graphics processor units (GPUs). We exploit the high computational power and memory ba...
Naga K. Govindaraju, Nikunj Raghuvanshi, Dinesh Ma...