Invention Grant
- Patent Title: Predicting labels using a deep-learning model
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Application No.: US14949436Application Date: 2015-11-23
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Publication No.: US10387464B2Publication Date: 2019-08-20
- Inventor: Jason E. Weston , Keith Adams , Sumit Chopra
- Applicant: Facebook, Inc.
- Applicant Address: US CA Menlo Park
- Assignee: Facebook, Inc.
- Current Assignee: Facebook, Inc.
- Current Assignee Address: US CA Menlo Park
- Agency: Baker Botts L.L.P.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06F16/33

Abstract:
In one embodiment, a method includes receiving text query that includes n-grams. A vector representation of each n-gram is determined using a deep-learning model. A nonlinear combination of the vector representations of the n-grams is determined, and an embedding of the text query is determined based on the nonlinear combination. The embedding of the text query corresponds to a point in an embedding space, and the embedding space includes a plurality of points corresponding to a plurality of label embeddings. Each label embedding is based on a vector representation of a respective label determined using the deep-learning model. Label embeddings are identified as being relevant to the text query by applying a search algorithm to the embedding space. Points corresponding to the identified label embeddings are within a threshold distance of the point corresponding to the embedding of the text query in the embedding space.
Public/Granted literature
- US20170061294A1 Predicting Labels Using a Deep-Learning Model Public/Granted day:2017-03-02
Information query