The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 10, 2020

Filed:

Oct. 23, 2018
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Ranit Aharonov, Ramat Hasharon, IL;

Liat Ein Dor, Tel-Aviv, IL;

Alon Halfon, Fishon Lezion, IL;

Yosi Mass, Ramat Gan, IL;

Ilya Shnayderman, Jerusalem, IL;

Noam Slonim, Jerusalem, IL;

Elad Venezian, Ramat Gan, IL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01); G06F 16/31 (2019.01); G06N 3/04 (2006.01); G06K 9/62 (2006.01); G06F 40/20 (2020.01);
U.S. Cl.
CPC ...
G06F 16/313 (2019.01); G06F 40/20 (2020.01); G06K 9/6215 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01);
Abstract

A method of estimating a thematic similarity of sentences, comprising receiving a corpus of a plurality of documents describing a plurality of topics where each document comprises a plurality of sentences arranged in a plurality of sections, constructing sentence triplets for at least some of the sentences, each sentence triplet comprising a respective sentence, a respective positive sentence selected randomly from the section comprising the respective sentence and a respective negative sentence selected randomly from another section, training a first neural network with the sentence triplets to identify sentence-sentence vectors mapping each sentence with a shorter distance to its respective positive sentence compared to the distance to its respective negative sentence and outputting the first neural network for estimating thematic similarity between a pair of sentences by computing a distance between the sentence-sentence vectors produced for each sentence of the pair by the first neural network.


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