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» Mining Developing Trends of Dynamic Spatiotemporal Data Stre...
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SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
12 years 8 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham
PAKDD
2010
ACM
171views Data Mining» more  PAKDD 2010»
13 years 3 months ago
Summarizing Multidimensional Data Streams: A Hierarchy-Graph-Based Approach
With the rapid development of information technology, many applications have to deal with potentially infinite data streams. In such a dynamic context, storing the whole data stre...
Yoann Pitarch, Anne Laurent, Pascal Poncelet
KDD
2007
ACM
178views Data Mining» more  KDD 2007»
14 years 5 months ago
Density-based clustering for real-time stream data
Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Yixin Chen, Li Tu
PREMI
2007
Springer
13 years 11 months ago
Discovery of Process Models from Data and Domain Knowledge: A Rough-Granular Approach
The rapid expansion of the Internet has resulted not only in the ever-growing amount of data stored therein, but also in the burgeoning complexity of the concepts and phenomena per...
Andrzej Skowron
KDD
2009
ACM
224views Data Mining» more  KDD 2009»
13 years 9 months ago
Issues in evaluation of stream learning algorithms
Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
João Gama, Raquel Sebastião, Pedro P...