Duquesne University of the Holy Spirit

Duquesne University of the Holy Ghost

Ryan, Michael

Juola, Patrick

Gray, Christine

Overly, James Orlo

Noecker, John Isaac

Patrick Juola

Michael C Ryan

Michael Stephen Ryan

John Isaac Noecker, Jr

Christine Gray

James Orlo Overly

John Isaac Noecker

Novel distractorless authorship verification technology optionally combines with novel algorithms to solve authorship attribution as to an open set of candidates&#x2014;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=p&#x2212;p&#x221a; p+p&#x2212;(p&#x2212;p)/n) is larger than a first predetermined threshold then author j cannot be the correct author; or if z (z=p&#x2212;p&#x221a; p+p&#x2212;(p&#x2212;p)/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&#x2014;in a number of novel applications. Personality profiling and authorship attribution may also be used to verify user identity to a computer.

Authorship technologies

Novel distractorless authorship verification technology optionally combines with novel algorithms to solve authorship attribution as to an open set of candidates&#x2014;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=p&#x2212;p&#x221a;p+p&#x2212;(p&#x2212;p)/n) is larger than a first predetermined threshold then author j cannot be the correct author; or if z (z=p&#x2212;p&#x221a;p+p&#x2212;(p&#x2212;p)/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&#x2014;in a number of novel applications. Personality profiling and authorship attribution may also be used to verify user identity to a computer.

A method for identifying an animal or human, including the steps of collecting and retaining an archive data set of measurements of two or more kinetic stylometrics of a first individual animal or human; collecting and retaining a test data set of measurements of the same two or more kinetic stylometrics of a test individual; and comparing archive and test data sets to determine similarity therefore, wherein similarity within any appropriate confidence interval confirms that the test individual and the first individual are the same. Using similar methods, social or other groups maybe kinetically stylometrically profiled for subsequent individual testing.

Kinetic-based tool for biometric identification, verification, validation and profiling

A computerized data processing system for categorizing documents that applies candidate functions, such as entropy, cross-entropy, and KL-distance, to data classification is disclosed. A computerized method for categorizing documents employing the candidate functions is also disclosed. The computerized data processing system and method of this invention allows for the automatic categorization, retrieval, and filtration of documents based upon the degree and/or rate of divergence from a reference standard.

Document categorization and evaluation via cross-entrophy

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Pittsburgh, PA, United States of America

Patrick Juola