Composite propensity profile detector

A system for detecting propensity profile for a person, comprising:

• a processor comprising at least hardware;
• one or more profile characteristic detectors operable to execute on the processor, and further operable to detect profile characteristics for the person based on a plurality of received artifacts, the profile characteristics comprising changes over time of at least personality and emotional state of the person;
• and
• a profile matcher operable to execute on the processor, and further operable to match by executing a machine learning algorithm, the profile characteristics for the person with one or more of a plurality of predefined profiles, the 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, the profile matcher further operable to output 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,
• wherein one or more latent characteristics determined based on performing a what-if analysis is added to the profile characteristics, 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.

A non-transitory computer readable storage medium storing a program of instructions executable by a machine to perform a method of detecting propensity profile for a person, the method comprising:

• receiving artifacts associated with the person;
• detecting 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 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.