Learning to rank using gradient descent
Top Cited Papers
- 1 January 2005
- proceedings article
- Published by Association for Computing Machinery (ACM)
Abstract
We investigate using gradient descent meth- ods for learning ranking functions; we pro- pose a simple probabilistic cost function, and we introduce RankNet, an implementation of these ideas using a neural network to model the underlying ranking function. We present test results on toy data and on data from a commercial internet search engine.Keywords
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