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ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 4 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
134
Voted
VLDB
1994
ACM
140views Database» more  VLDB 1994»
15 years 7 months ago
Efficient and Effective Clustering Methods for Spatial Data Mining
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering ...
Raymond T. Ng, Jiawei Han
ICDM
2005
IEEE
122views Data Mining» more  ICDM 2005»
15 years 9 months ago
ViVo: Visual Vocabulary Construction for Mining Biomedical Images
Given a large collection of medical images of several conditions and treatments, how can we succinctly describe the characteristics of each setting? For example, given a large col...
Arnab Bhattacharya, Vebjorn Ljosa, Jia-Yu Pan, Mar...
KDD
1998
ACM
190views Data Mining» more  KDD 1998»
15 years 7 months ago
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
R. Bharat Rao, Scott Rickard, Frans Coetzee
128
Voted
SIGMOD
2010
ACM
260views Database» more  SIGMOD 2010»
15 years 8 months ago
Towards proximity pattern mining in large graphs
Mining graph patterns in large networks is critical to a variety of applications such as malware detection and biological module discovery. However, frequent subgraphs are often i...
Arijit Khan, Xifeng Yan, Kun-Lung Wu