Papers › Personalized Language Model for Query Auto-Completion

Personalized Language Model for Query Auto-Completion

25 Apr 2018ACL 2018 7arXiv:1804.09661archive 2025-07-28

Aaron Jaech, Mari Ostendorf

Query auto-completion is a search engine feature whereby the system suggests completed queries as the user types. Recently, the use of a recurrent neural network language model was suggested as a method of generating query completions. We show how an adaptable language model can be used to generate personalized completions and how the model can use online updating to make predictions for users not seen during training. The personalized predictions are significantly better than a baseline that uses no user information.

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