Authorship Technologies

Patent №

US 10,657,494

Granted

2020-05-19

Filed 2014

Owner

DUQUESNE UNIVERSITY OF THE HOLY SPIRIT

Lab

AI components

3

ml · nlp · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

14114956

Novel distractorless authorship verification technology optionally combines with novel algorithms to solve authorship attribution as to an open set of candidates—such as without limitation by analyzing the voting of “mixture of experts” and outputting the result to a user using the following: if z (z=pi−pj√pi+pj−(pi−pj)2/n) is larger than a first predetermined threshold then author j cannot be the correct author; or if z (z=pi−pj√pi+pj−(pi−pj)2/n) is smaller than a second predetermined threshold then author i cannot be the correct author; or if no author garners significantly more votes than all other contenders then none of the named authors is the author of a document in question—in a number of novel applications. Personality profiling and authorship attribution may also be used to verify user identity to a computer.

Machine learningNatural languageAI hardwareG06Q 10/10G06F 21/31G06F 40/253G06Q 50/184G06F 2221/2131

AI classification

Natural language1.00
Machine learning0.99
AI hardware0.77
Knowledge representation0.01
Vision0.01
Planning0.01
Evolutionary computation0.00
Speech0.00

Ownership

DUQUESNE UNIVERSITY OF THE HOLY SPIRIT

assignment · 286350479

Assignors

JUOLA, PATRICK, OVERLY, JAMES O, NOECKER, JOHN ISAAC, JR, RYAN, MICHAEL, GRAY, CHRISTINE, JUOLA, PATRICK, OVERLY, JAMES O, NOECKER, JOHN ISAAC, JR., RYAN, MICHAEL, GRAY, CHRISTINE

On an employer assignment, the assignors are typically the inventors.

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