Blending learning models for search support
Abstract:
A method and apparatus of a device that generates a re-ranking model used to re-rank a plurality of search results on a client device is described. In an exemplary embodiment, the device receives a crowd-sourced intra-domain model from a server, where the intra-domain model is a search result re-ranking model generated based on at least device interactions of a plurality of users interacting with a plurality of other devices. The device further generates a re-ranking model from the crowd-sourced intra-domain model and a local model, where the local model includes private data representing a device user's interaction with that device and the re-ranking model is used to re-rank a plurality of search results.
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