Abstract A ranking model utilizing the multiple hyperplanes optimized by the order relations is proposed based on RankSVM in this paper. Firstly, the multiple hyperplanes are built based on the order relations between the ranks for training data in this model. Then, the ranking list generated by multiple hyperplanes is aggregated to gain the final ranking results. The proposed model is tested on LETOR OHSUMED dataset, some typical indices in Information Retrieval field being applied to evaluate its performance and the method being compared with other methods such as RankSVM. The experimental results show that the model not only has better ranking performance but also shorten the training time evidently.
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2010, Vol. 23 
