Abstract: A computer readable medium for analyzing images according to specific kinds of features oriented towards detecting subtle branding features (intentional or otherwise) rather than relying on the usual image similarity detection methods. Also disclosed are steps to enhance standard machine learning techniques to identify new types of transformations by partitioning data into measure-countermeasure windows, which may be either/both detected computationally or inputted into a knowledgebase. The invention further incorporates direct and indirect traits of images that were likely to have been promulgated by a particular group or actor of interest, especially those traits that prove to be more invariant over time (including the use of transformations) which have proven to be more resistant to countermeasures applied in different jurisdictions. More generally, almost all embodiments allow individual feature calculations to be toggled on and off, and to define sets of features according to jurisdiction.
Type:
Grant
Filed:
September 19, 2019
Date of Patent:
February 28, 2023
Assignee:
Chenope, Inc.
Inventors:
Elizabeth B. Charnock, Steven L. Roberts
Abstract: A computer readable medium for analyzing and predicting the future behavior of organizations is disclosed. An embodiment of this invention is comprised of one or more repositories of data which involve comments or other actions by actors with some kind of relationship to a target organization, a repository of metadata relating to this data, a repository of updatable models of organizations, a natural language parsing engine, and an engine for generating and comparing the organizational models.
Type:
Grant
Filed:
July 20, 2016
Date of Patent:
February 14, 2017
Assignee:
Chenope, Inc.
Inventors:
Richard Oehrle, Steven Lee Roberts, Elizabeth B Charnock, Katya Saint-Amand, Laurent Jean-Marc Guillaume Dupont