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» Learning to rank on graphs
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IR
2010
14 years 8 months ago
LETOR: A benchmark collection for research on learning to rank for information retrieval
LETOR is a benchmark collection for the research on learning to rank for information retrieval, released by Microsoft Research Asia. In this paper, we describe the details of the L...
Tao Qin, Tie-Yan Liu, Jun Xu, Hang Li
VLDB
2004
ACM
138views Database» more  VLDB 2004»
15 years 3 months ago
ObjectRank: Authority-Based Keyword Search in Databases
The ObjectRank system applies authority-based ranking to keyword search in databases modeled as labeled graphs. Conceptually, authority originates at the nodes (objects) containin...
Andrey Balmin, Vagelis Hristidis, Yannis Papakonst...
ICCV
2009
IEEE
14 years 7 months ago
Efficient multi-label ranking for multi-class learning: Application to object recognition
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
Serhat Selcuk Bucak, Pavan Kumar Mallapragada, Ron...
PPSN
2004
Springer
15 years 3 months ago
Ensemble Learning with Evolutionary Computation: Application to Feature Ranking
Abstract. Exploiting the diversity of hypotheses produced by evolutionary learning, a new ensemble approach for Feature Selection is presented, aggregating the feature rankings ext...
Kees Jong, Elena Marchiori, Michèle Sebag
IJCNN
2006
IEEE
15 years 3 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang