Factor Models for Recommending Given Names
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چکیده
We describe in this paper our contribution to the ECML PKDD Discovery Challenge 2013 (Offline Track). This years task was to predict the next given names a user of a name search engine interacts with. We model the user preferences with a sequential factor model that we optimize with respect to the Bayesian Personalized Ranking (BPR) Optimization Criterion. Therefore we complement the sequential factor model with prefix smoothing in order to explicitly model syntactical similarity.
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تاریخ انتشار 2013