Patent ID: 9311467
Filing Date: 2016-04-12
CPC Classification: G06F,G06N,H04L

Claim Text:
1. A method for detecting propensity profile of a person, comprising: receiving artifacts associated with the person; detecting, by one or more computer processors, profile characteristics for the person based on the artifacts, the profile characteristics comprising changes over time of at least personality and emotional state of the person; receiving a plurality of predefined profiles comprising a plurality of characteristics and relationships between the characteristics over time wherein at least some of the characteristics have time varying interdependencies among one another, each of the plurality of predefined profiles specifying an indication of propensity; matching, by one or more of the computer processors executing a machine learning algorithm, the profile characteristics for the person with one or more of the plurality of predefined profiles; and outputting one or more propensity indicators based on the matching, the propensity indicators comprising at least an expressed strength of a given propensity in the person at a given time, adding one or more latent characteristics to the profile characteristics determined based on performing a what-if analysis, for detecting whether combining the one or more latent characteristics with the profile characteristics at the given time would trigger a propensity indication which would not be triggered by the profile characteristics.