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IJCNN
2008
IEEE
15 years 8 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...
113
Voted
CVPR
2006
IEEE
16 years 3 months ago
AnnoSearch: Image Auto-Annotation by Search
Although it has been studied for several years by computer vision and machine learning communities, image annotation is still far from practical. In this paper, we present AnnoSea...
Xin-Jing Wang, Lei Zhang, Feng Jing, Wei-Ying Ma
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
15 years 7 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
117
Voted
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
15 years 11 months ago
On Segment-Based Stream Modeling and Its Applications.
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
Charu C. Aggarwal
126
Voted
NIPS
2008
15 years 3 months ago
Spectral Clustering with Perturbed Data
Spectral clustering is useful for a wide-ranging set of applications in areas such as biological data analysis, image processing and data mining. However, the computational and/or...
Ling Huang, Donghui Yan, Michael I. Jordan, Nina T...