Abstract: The present invention implements, in a trend or pattern trigger device or system, the generation of hypotheses automatically while considering any collection of data by automatically assessing with templates or charts the presence of patterns in the data without a priori postulation of what the pattern might be. The trend or pattern examination templates or charts contain quantifiable thresholds for data or change in data so that trends or patterns in data can be discerned inductively and automatically without preconceived notions of what or where the patterns or trends might be.

Abstract: The present invention is an automated data-extractor which is pre-set to extract specified data from a user's personal device (such as but not limited to a smart phone), and then to present that extracted data to the user for verification by recognition, not by recall, as part of a security log-in protocol. Recognition is much easier, for a user, than outright recall, and therefore the present technology provides a user-friendly way to verify an individual during a log-in procedure. The invention thus embraces at least a two modules containing (a) a data extractor module and (b) a combination generator module which presents the extracted data to the user in a question-and-answer mode to prompt “yes” or “no” verification of the data extracted, but requiring only recognition as to the user's own data, not completely unprompted recall.

Abstract: The instant document converter transforms any text or text-predominant document, virtually immediately and automatically, to a list containing solely its culled, formatted references, together with one or more coordinated executables that launch the culled formatted references as a search query, when triggered, to a search engine for verification analysis.

Abstract: The present invention is a modular electromechanical system for proctoring an online examination, as to a test-taker at a remote computer location, incorporating modules which collect and compare only motion-detected biometrics. The modules of the system include a computer keyboard or equivalent input device, a User Registration Database, a module for motion sensing (during testing) and data transmission that populates a Motion Capture Database, and a compiler for comparing or contrasting the User Registration Database and the Motion Capture Database, with the compiler's rendering its analytical data to a Secure Compilation Database Storage with User Output. The User Registration Database is populated in advance of the test to be proctored, in a secure setting.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The present invention implements, in a trend or pattern trigger device or system, the generation of hypotheses automatically while considering any collection of data by automatically assessing with templates or charts the presence of patterns in the data without a priori postulation of what the pattern might be. The trend or pattern examination templates or charts contain quantifiable thresholds for data or change in data so that trends or patterns in data can be discerned inductively and automatically without preconceived notions of what or where the patterns or trends might be.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The present invention implements, in a trend or pattern trigger device or system, the generation of hypotheses automatically while considering any collection of data by automatically assessing with templates or charts the presence of patterns in the data without a priori postulation of what the pattern might be. The trend or pattern examination templates or charts contain quantifiable thresholds for data or change in data so that trends or patterns in data can be discerned inductively and automatically without preconceived notions of what or where the patterns or trends might be.

Abstract: 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.