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112
Voted
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 1 months ago
A probabilistic framework for relational clustering
Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such...
Bo Long, Zhongfei (Mark) Zhang, Philip S. Yu
104
Voted
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
16 years 1 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
KDD
2006
ACM
253views Data Mining» more  KDD 2006»
16 years 1 months ago
Adaptive Website Design Using Caching Algorithms
Visitors enter a website through a variety of means, including web searches, links from other sites, and personal bookmarks. In some cases the first page loaded satisfies the visi...
Justin Brickell, Inderjit S. Dhillon, Dharmendra S...
128
Voted
KDD
2005
ACM
218views Data Mining» more  KDD 2005»
16 years 1 months ago
A maximum entropy web recommendation system: combining collaborative and content features
Web users display their preferences implicitly by navigating through a sequence of pages or by providing numeric ratings to some items. Web usage mining techniques are used to ext...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
140
Voted
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
16 years 1 months ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle