Patents by Inventor Robin JIA

Robin JIA has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10943068
    Abstract: A computing system is provided. The computing system includes a processor configured to execute one or more programs and associated memory. The processor is configured to execute neural network system that includes a first neural network and a second neural network. The processor is configured to receive input text, and for each of a plurality of text spans within the input text: identify a vector of semantic entities and a vector of entity mentions; define an n-ary relation between entity mentions including subrelations; and determine mention-level representation vectors in the text spans that satisfy the n-ary relation or subrelations. The processor is configured to: aggregate the mention-level representation vectors over all of the text spans to produce entity-level representation vectors; input to the second neural network the entity-level representation vectors; and output a prediction of a presence of the n-ary relation for the semantic entities in the input text.
    Type: Grant
    Filed: March 29, 2019
    Date of Patent: March 9, 2021
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Hoifung Poon, Cliff Wong, Robin Jia
  • Publication number: 20200311198
    Abstract: A computing system is provided. The computing system includes a processor configured to execute one or more programs and associated memory. The processor is configured to execute neural network system that includes a first neural network and a second neural network. The processor is configured to receive input text, and for each of a plurality of text spans within the input text: identify a vector of semantic entities and a vector of entity mentions; define an n-ary relation between entity mentions including subrelations; and determine mention-level representation vectors in the text spans that satisfy the n-ary relation or subrelations. The processor is configured to: aggregate the mention-level representation vectors over all of the text spans to produce entity-level representation vectors; input to the second neural network the entity-level representation vectors; and output a prediction of a presence of the n-ary relation for the semantic entities in the input text.
    Type: Application
    Filed: March 29, 2019
    Publication date: October 1, 2020
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Hoifung POON, Cliff WONG, Robin JIA