Adapting deep RankNet for personalized search Adapting deep RankNet for personalized search
Paper summary [Adapting Deep RankNet for Personalized Search](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/wsdm233-song.pdf) is a paper published in 2014 by Song, Wang and He from Microsoft Research. It is heavily beased on [Learning to rank using gradient descent](https://www.shortscience.org/paper?bibtexKey=conf/icml/BurgesSRLDHH05) (Burges et al from Microsoft, 2005). They use a neural network with 5 hidden layers. They investigate regularization by trunkated gradient and limiting the depth of the back propagation. ## See also * July 2015: [RankNet: A ranking retrospective](https://www.microsoft.com/en-us/research/blog/ranknet-a-ranking-retrospective/)
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Adapting deep RankNet for personalized search
Song, Yang and Wang, Hongning and He, Xiaodong
ACM WSDM - 2014 via Local Bibsonomy
Keywords: dblp


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Summary by Martin Thoma 3 months ago
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