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ICML
2010
IEEE
15 years 28 days ago
Metric Learning to Rank
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Brian McFee, Gert R. G. Lanckriet
PAKDD
2009
ACM
94views Data Mining» more  PAKDD 2009»
15 years 4 months ago
Item Preference Parameters from Grouped Ranking Observations
Given a set of rating data for a set of items, determining the values of items is a matter of importance and various probability models have been proposed. The Plackett-Luce model ...
Hideitsu Hino, Yu Fujimoto, Noboru Murata
CIKM
2010
Springer
14 years 10 months ago
Computing the top-k maximal answers in a join of ranked lists
Complex search tasks that utilize information from several data sources, are answered by integrating the results of distinct basic search queries. In such integration, each basic ...
Mirit Shalem, Yaron Kanza
ICALT
2010
IEEE
14 years 10 months ago
Course Ranking and Automated Suggestions through Web Mining
—This paper introduces new metrics for course evaluation. It is also proposes a ranking algorithm that classifies courses based on the previous course evaluation metrics and sugg...
Stavros Valsamidis, Ioannis Kazanidis, Sotirios Ko...
ICML
2005
IEEE
16 years 20 days ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic