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US Patent 10402495 Abstractive sentence summarization

Patent 10402495 was granted and assigned to Facebook on September, 2019 by the United States Patent and Trademark Office.

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Contents

Is a
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
104024950
Patent Inventor Names
Jason Edward Weston0
Sumit Chopra0
Alexander Matthew Rush0
Date of Patent
September 3, 2019
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Patent Application Number
156940310
Date Filed
September 1, 2017
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Patent Citations
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US Patent 10083157 Text classification and transformation based on author
Patent Citations Received
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US Patent 12130851 Method and system for improving performance of text summarization
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US Patent 10984247 Accurate correction of errors in text data based on learning via a neural network
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US Patent 10990765 Sentence generating method and apparatus
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US Patent 11010142 User interface
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US Patent 11651161 Automated detection of reasoning in arguments
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US Patent 11803751 Training text summarization neural networks with an extracted segments prediction objective
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US Patent 11520971 System and method for artificial intelligence story generation allowing content introduction
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US Patent 10572604 Sentence generating method and apparatus
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...
Patent Primary Examiner
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Satwant K Singh
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Patent abstract

In one embodiment, a sequence of input words is received. Each of the input words is encoded as an indicator vector, wherein a sequence of the indicator vectors captures features of the sequence of input words. The sequence of the indicator vectors is then mapped to a distribution of a contextual probability of a first output word in a sequence of output words. For each subsequent output word, the sequence of the indicator vectors is encoded with a context, wherein the context comprises a previously mapped contextual probability distribution of a fixed window of previous output words; and the encoded sequence of the indicator vectors and the context is mapped to the distribution of the contextual probability of the subsequent output word. Finally, a condensed summary is generated using a decoder by maximizing the contextual probability of each of the output words.

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