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MACHINE LEARNING MODELS WITH IMPROVED SEMANTIC AWARENESS

  • Oren Sar Shalom (Inventor)
  • , Alexander Zhicharevich (Inventor)
  • , Adi Shalev (Inventor)
  • , Yehezkel Shraga Resheff (Inventor)

Research output: Patent

Abstract

[0001] A method including inputting, into a phrase recognition model comprising a neural network, a vector comprising a plurality of ngrams of text. The method also includes applying, using the phrase recognition model, a filter to the plurality of ngrams during execution. The filter has a skip word setting of at least one. The method also includes determining, based on the skip word setting, at least one ngram in the vector to be skipped to form at least one skip word. The method also includes outputting an intermediate score for a set of ngrams that match the filter. The method also includes calculating a scalar number representing a semantic meaning of the at least one skip word. The method also includes generating based on the scalar number and the intermediate score, a final score for the set of ngrams. A computer action is performed using the final score.

Original languageEnglish
Patent numberUS11875116
IPCG06F 40/ 30 A I
Priority date20/12/19
StatePublished - 24 Jun 2021

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