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» Phenomenal Data Mining: From Data to Phenomena
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KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 1 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
16 years 1 months ago
Cost-effective outbreak detection in networks
Given a water distribution network, where should we place sensors to quickly detect contaminants? Or, which blogs should we read to avoid missing important stories? These seemingl...
Andreas Krause, Carlos Guestrin, Christos Faloutso...
KDD
2002
ACM
170views Data Mining» more  KDD 2002»
16 years 1 months ago
Enhanced word clustering for hierarchical text classification
In this paper we propose a new information-theoretic divisive algorithm for word clustering applied to text classification. In previous work, such "distributional clustering&...
Inderjit S. Dhillon, Subramanyam Mallela, Rahul Ku...
WSDM
2010
ACM
251views Data Mining» more  WSDM 2010»
15 years 10 months ago
Large Scale Query Log Analysis of Re-Finding
Although Web search engines are targeted towards helping people find new information, people regularly use them to re-find Web pages they have seen before. Researchers have noted ...
Jaime Teevan, Sarah K. Tyler
WSDM
2009
ACM
115views Data Mining» more  WSDM 2009»
15 years 8 months ago
Discovering and using groups to improve personalized search
Personalized Web search takes advantage of information about an individual to identify the most relevant results for that person. A challenge for personalization lies in collectin...
Jaime Teevan, Meredith Ringel Morris, Steve Bush