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IWPEC
2010
Springer
14 years 7 months ago
Partial Kernelization for Rank Aggregation: Theory and Experiments
RANK AGGREGATION is important in many areas ranging from web search over databases to bioinformatics. The underlying decision problem KEMENY SCORE is NP-complete even in case of fo...
Nadja Betzler, Robert Bredereck, Rolf Niedermeier
ISNN
2009
Springer
15 years 4 months ago
A New Instance-Based Label Ranking Approach Using the Mallows Model
In this paper, we introduce a new instance-based approach to the label ranking problem. This approach is based on a probability model on rankings which is known as the Mallows mode...
Weiwei Cheng, Eyke Hüllermeier
NAACL
2007
14 years 11 months ago
Multiple Aspect Ranking Using the Good Grief Algorithm
We address the problem of analyzing multiple related opinions in a text. For instance, in a restaurant review such opinions may include food, ambience and service. We formulate th...
Benjamin Snyder, Regina Barzilay
ALT
2008
Springer
15 years 6 months ago
Smooth Boosting for Margin-Based Ranking
We propose a new boosting algorithm for bipartite ranking problems. Our boosting algorithm, called SoftRankBoost, is a modification of RankBoost which maintains only smooth distri...
Jun-ichi Moribe, Kohei Hatano, Eiji Takimoto, Masa...
ICML
2007
IEEE
15 years 10 months ago
Learning to rank: from pairwise approach to listwise approach
The paper is concerned with learning to rank, which is to construct a model or a function for ranking objects. Learning to rank is useful for document retrieval, collaborative fil...
Zhe Cao, Tao Qin, Tie-Yan Liu, Ming-Feng Tsai, Han...