Detecting non-obvious relationships between entities from visual data sources

A computer program product incorporated into a risk analysis application, the computer program product comprising:

• one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions comprising:
• program instructions to calculate a co-occurrence frequency score for an entity pair from the visual data;
• program instructions to calculate a distance proximity score for the entity pair from the visual data;
• program instructions to determine an event type in the visual data based on event metadata indicating an environment setting including a nature of the event, information of the number of attendees and a background scene;
• program instructions to determine a timeline relationship in the visual data by determining an initial point of a co-occurrence of the entity pair, a frequency of the co-occurrence over time, a time gap in which the co-occurrence does not occur, and the most recent point of the co-occurrence;
• program instructions to calculate a relationship score based on the co-occurrence frequency score, the distance proximity score, the event type, and the timeline relationship;
• program instructions to adjust the relationship score, in a risk analysis application, based on changing weighting values of parameters comprising the co-occurrence frequency score, the distance proximity score, the event type and the timeline relationship, after a relationship risk analysis;
• and
• program instructions to detect a relationship between the entity pair based on the relationship score.

A computer system incorporated into a risk analysis application, the computer system comprising:

• one or more computer processors, one or more computer readable storage media, and program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising:
• program instructions to calculate a co-occurrence frequency score for an entity pair from the visual data;
• program instructions to calculate a distance proximity score for the entity pair from the visual data;
• program instructions to determine an event type in the visual data based on event metadata indicating an environment setting including a nature of the event, information of the number of attendees and a background scene;
• program instructions to determine a timeline relationship in the visual data by determining an initial point of a co-occurrence of the entity pair, a frequency of the co-occurrence over time, a time gap in which the co-occurrence does not occur, and the most recent point of the co-occurrence;
• program instructions to calculate a relationship score based on the co-occurrence frequency score, the distance proximity score, the event type, and the timeline relationship;
• program instructions to adjust the relationship score, in a risk analysis application, based on changing weighting values of parameters comprising the co-occurrence frequency score, the distance proximity score, the event type and the timeline relationship, after a relationship risk analysis;
• and
• program instructions to detect a relationship between the entity pair based on the relationship score.