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INTR
2010
157views more  INTR 2010»
13 years 6 months ago
Classifying the user intent of web queries using k-means clustering
Purpose – Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, so...
Ashish Kathuria, Bernard J. Jansen, Carolyn Hafern...
KAIS
2002
144views more  KAIS 2002»
13 years 7 months ago
Correlation-Based Web Document Clustering for Adaptive Web Interface Design
A great challenge for web site designers is how to ensure users' easy access to important web pages efficiently. In this paper we present a clustering-based approach to addres...
Zhong Su, Qiang Yang, HongJiang Zhang, Xiaowei Xu,...
PR
2006
164views more  PR 2006»
13 years 7 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung
ICWS
2009
IEEE
14 years 5 months ago
Adaptive Prefetching Scheme Using Web Log Mining in Cluster-Based Web Systems
The main memory management has been a critical issue to provide high performance in web cluster systems. To overcome the speed gap between processors and disks, many prefetch sche...
Heung Ki Lee, Baik Song An, Eun Jung Kim
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 8 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu