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» Learning to Rank with Supplementary Data
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ICML
2006
IEEE
14 years 8 months ago
Learning user preferences for sets of objects
Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Marie desJardins, Eric Eaton, Kiri Wagstaff
KDD
2007
ACM
210views Data Mining» more  KDD 2007»
14 years 2 months ago
Machine learning for stock selection
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
Robert J. Yan, Charles X. Ling
WWW
2007
ACM
14 years 8 months ago
Measuring credibility of users in an e-learning environment
Learning Villages (LV) is an E-learning platform for people's online discussions and frequently citing postings of one another. In this paper, we propose a novel method to ra...
Wei Wei, Jimmy Ho-Man Lee, Irwin King
ICML
2003
IEEE
14 years 8 months ago
Online Ranking/Collaborative Filtering Using the Perceptron Algorithm
In this paper we present a simple to implement truly online large margin version of the Perceptron ranking (PRank) algorithm, called the OAP-BPM (Online Aggregate Prank-Bayes Poin...
Edward F. Harrington
SIGIR
2009
ACM
14 years 2 months ago
Global ranking by exploiting user clicks
It is now widely recognized that user interactions with search results can provide substantial relevance information on the documents displayed in the search results. In this pape...
Shihao Ji, Ke Zhou, Ciya Liao, Zhaohui Zheng, Gui-...