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» Mining preferences from superior and inferior examples
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KDD
2008
ACM
110views Data Mining» more  KDD 2008»
14 years 5 months ago
Mining preferences from superior and inferior examples
Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing camp...
Bin Jiang, Jian Pei, Xuemin Lin, David W. Cheung, ...
ICTAI
2010
IEEE
13 years 2 months ago
Argumentation for Aggregating Clinical Evidence
Abstract--Evidence-based decision making is becoming increasingly important in healthcare. Much valuable evidence is in the form of the results from clinical trials that compare th...
Anthony Hunter, Matthew Williams
ICPR
2006
IEEE
14 years 5 months ago
Scalable Representative Instance Selection and Ranking
Finding a small set of representative instances for large datasets can bring various benefits to data mining practitioners so they can (1) build a learner superior to the one cons...
Xindong Wu, Xingquan Zhu
KDD
2004
ACM
148views Data Mining» more  KDD 2004»
14 years 5 months ago
Spying Out Accurate User Preferences for Search Engine Adaptation
Abstract. Most existing search engines employ static ranking algorithms that do not adapt to the specific needs of users. Recently, some researchers have studied the use of clickth...
Lin Deng, Wilfred Ng, Xiaoyong Chai, Dik Lun Lee
PKDD
2010
Springer
183views Data Mining» more  PKDD 2010»
13 years 2 months ago
Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes
Abstract. In preference learning, the algorithm observes pairwise relative judgments (preference) between items as training data for learning an ordering of all items. This is an i...
Zhao Xu, Kristian Kersting, Thorsten Joachims