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ICDM
2008
IEEE
252views Data Mining» more  ICDM 2008»
15 years 7 months ago
Data Mining for Climate Change and Impacts
Knowledge discovery from temporal, spatial and spatiotemporal data is critical for climate change science and climate impacts. Climate statistics is a mature area. However, recent...
Auroop R. Ganguly, Karsten Steinhaeuser
ECCV
2006
Springer
15 years 4 months ago
Spatial Segmentation of Temporal Texture Using Mixture Linear Models
In this paper we propose a novel approach for the spatial segmentation of video sequences containing multiple temporal textures. This work is based on the notion that a single tem...
Lee Cooper, Jun Liu, Kun Huang
WMCSA
2003
IEEE
15 years 5 months ago
Proximity Mining: Finding Proximity using Sensor Data History
Emerging ubiquitous and pervasive computing applications often need to know where things are physically located. To meet this need, many locationsensing systems have been develope...
Toshihiro Takada, Satoshi Kurihara, Toshio Hirotsu...
INCDM
2010
Springer
208views Data Mining» more  INCDM 2010»
15 years 2 months ago
Combining Unsupervised and Supervised Data Mining Techniques for Conducting Customer Portfolio Analysis
Abstract. Leveraging the power of increasing amounts of data to analyze customer base for attracting and retaining the most valuable customers is a major problem facing companies i...
Zhiyuan Yao, Annika H. Holmbom, Tomas Eklund, Barb...
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
16 years 26 days ago
SPIN: mining maximal frequent subgraphs from graph databases
One fundamental challenge for mining recurring subgraphs from semi-structured data sets is the overwhelming abundance of such patterns. In large graph databases, the total number ...
Jun Huan, Wei Wang 0010, Jan Prins, Jiong Yang