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...
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...
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...
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...
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...