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US Patent 10558759 Consumer insights analysis using word embeddings

Patent 10558759 was granted and assigned to Facebook on February, 2020 by the United States Patent and Trademark Office.

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Patent
Patent
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Patent attributes

Patent Applicant
Facebook
Facebook
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Current Assignee
Facebook
Facebook
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
105587590
Patent Inventor Names
Shriram Subramanian0
Bryan Kauder0
Jonathan Michael Arfa0
Nikhil Girish Nawathe0
Alyx Catherine Stevens0
Date of Patent
February 11, 2020
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Patent Application Number
158620570
Date Filed
January 4, 2018
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Patent Citations Received
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US Patent 12072917 Database generation from natural language text documents
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US Patent 11636847 Ontology-augmented interface
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US Patent 11699432 Cross-context natural language model generation
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US Patent 11790889 Feature engineering with question generation
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US Patent 11854531 Cross-class ontology integration for language modeling
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US Patent 11860916 Database query generation using natural language text
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US Patent 11893355 Semantic map generation from natural-language-text documents
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US Patent 11960846 Embedding inference
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...
Patent Primary Examiner
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Andrew C Flanders
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Patent abstract

In one embodiment, a method includes receiving a request to generate k words that each approximates a representation of a relationship between two concepts, where the request includes two input n-grams that each represent one of the two concepts, accessing a table of word vector relationships, where the table includes a plurality of unique n-grams and their corresponding word vectors, looking up word vectors corresponding to each of the two input n-grams using the table, calculating an average vector of the word vectors corresponding to the two input n-grams, selecting, using the table and based on a similarity metric, k word vectors closest to the average vector in the embedding space, identifying, for each of the selected word vectors, a corresponding n-gram by looking up the selected word vector in the table, and sending a response message, the response message comprising the identified n-grams.

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