Invention Grant
- Patent Title: Systems and methods for neural language modeling
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Application No.: US15047532Application Date: 2016-02-18
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Publication No.: US10339440B2Publication Date: 2019-07-02
- Inventor: Andrew Trask , David Gilmore , Matthew Russell
- Applicant: Digital Reasoning Systems, Inc.
- Applicant Address: US TN Franklin
- Assignee: Digital Reasoning Systems, Inc.
- Current Assignee: Digital Reasoning Systems, Inc.
- Current Assignee Address: US TN Franklin
- Agency: Meunier Carlin & Curfman LLC
- Main IPC: G06N3/02
- IPC: G06N3/02 ; G06N3/04 ; G06N3/08 ; G06F17/27

Abstract:
In some aspects, the present disclosure relates to neural language modeling. In one embodiment, a computer-implemented neural network includes a plurality of neural nodes, where each of the neural nodes has a plurality of input weights corresponding to a vector of real numbers. The neural network also includes an input neural node corresponding to a linguistic unit selected from an ordered list of a plurality of linguistic units, and an embedding layer with a plurality of embedding node partitions. Each embedding node partition includes one or more neural nodes. Each of the embedding node partitions corresponds to a position in the ordered list relative to a focus term, is configured to receive an input from an input node, and is configured to generate an output. The neural network also includes a classifier layer with a plurality of neural nodes, each configured to receive the embedding outputs from the embedding layer, and configured to generate an output corresponding to a probability that a particular linguistic unit is the focus term.
Public/Granted literature
- US20160247061A1 Systems and Methods for Neural Language Modeling Public/Granted day:2016-08-25
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