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ICDE
2009
IEEE
202views Database» more  ICDE 2009»
16 years 6 months ago
Tracking High Quality Clusters over Uncertain Data Streams
Recently, data mining over uncertain data streams has attracted a lot of attentions because of the widely existed imprecise data generated from a variety of streaming applications....
Chen Zhang, Ming Gao, Aoying Zhou
KDD
1998
ACM
112views Data Mining» more  KDD 1998»
15 years 8 months ago
Evaluating Usefulness for Dynamic Classification
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
SIGMOD
1997
ACM
134views Database» more  SIGMOD 1997»
15 years 8 months ago
Scalable Parallel Data Mining for Association Rules
One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consu...
Eui-Hong Han, George Karypis, Vipin Kumar
GIS
2009
ACM
15 years 8 months ago
Dynamic network data exploration through semi-supervised functional embedding
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
Alexei Pozdnoukhov
KDD
2005
ACM
147views Data Mining» more  KDD 2005»
15 years 10 months ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu