Abstract: A microprocessor executable method and system for determining the semantic relatedness and meaning between at least two natural language sources is described in a prescribed context. Portions of natural languages are vectorized and mathematically processed to express relatedness as a calculated metric. The metric is associable to the natural language sources to graphically present the level of relatedness between at least two natural language sources. The metric may be re-determined with algorithms designed to compare the natural language sources with a knowledge data bank so the calculated metric can be ascertained with a higher level of certainty.

Abstract: A microprocessor executable method and system for determining the semantic relatedness and meaning between at least two natural language sources is described in a prescribed context. Portions of natural languages are vectorized and mathematically processed to express relatedness as a calculated metric. The metric is associable to the natural language sources to graphically present the level of relatedness between at least two natural language sources. The metric may be re-determined with algorithms designed to compare the natural language sources with a knowledge data bank so the calculated metric can be ascertained with a higher level of certainty.

Abstract: The present invention is a system and method for delivering optimized road maintenance analysis to a municipality. The instant innovation scans roadways for distressed street surfaces, damaged signage, and other less-than-optimal municipal assets. Data is collected by multiple municipal fleet vehicles as such vehicles drive upon roads within a municipality. Collected data are analyzed by a machine learning algorithm using criteria that most directly correspond to multi-year road quality predictions. The instant innovation provides to a user one or more suggestions and scenario results for roadway maintenance strategies based upon the data analysis.

Abstract: A microprocessor executable method and system for determining the semantic relatedness and meaning between at least two natural language sources is described in a prescribed context. Portions of natural languages are vectorized and mathematically processed to express relatedness as a calculated metric. The metric is associable to the natural language sources to graphically present the level of relatedness between at least two natural language sources. The metric may be re-determined with algorithms designed to compare the natural language sources with a knowledge data bank so the calculated metric can be ascertained with a higher level of certainty.

Abstract: A microprocessor executable method and system for determining the semantic relatedness and meaning between at least two natural language sources is described in a prescribed context. Portions of natural languages are vectorized and mathematically processed to express relatedness as a calculated metric. The metric is associable to the natural language sources to graphically present the level of relatedness between at least two natural language sources. The metric may be re-determined with algorithms designed to compare the natural language sources with a knowledge data bank so the calculated metric can be ascertained with a higher level of certainty.

Abstract: A system and methods directed to the authentication/verification of identification and other documents. Such documents may include identity cards, driver's licenses, passports, documents being used to show a proof of registration or certification, voter ballots, data entry forms, etc. The authentication or verification process may be performed for purposes of control of access to information, control of access to and/or use of a venue, a method of transport, or a service, for assistance in performing a security function, to establish eligibility for and enable provision of a government provided service or benefit, etc. The authentication or verification process may also or instead be performed for purposes of verifying a document itself as authentic so that the information it contains can confidently be assumed to be accurate and reliable.

Abstract: A microprocessor executable method and system for determining the semantic relatedness and meaning between at least two natural language sources is described in a prescribed context. Portions of natural languages are vectorized and mathematically processed to express relatedness as a calculated metric. The metric is associable to the natural language sources to graphically present the level of relatedness between at least two natural language sources. The metric may be re-determined with algorithms designed to compare the natural language sources with a knowledge data bank so the calculated metric can be ascertained with a higher level of certainty.