SYSTEMS AND METHODS FOR CONTEXT-BASED EVENT DETECTION AND DETERMINATION

1 . A system comprising:

a storage device; and

at least one processor coupled to the storage device, the storage device storing software instructions for controlling the at least one processor when executed by the at least one processor, the at least one processor being operative with the software instructions and being configured to:

maintain scenario modeling data related to a plurality of personal event scenarios;

perform operations to communicate with one or more computer systems over a network to receive personal event data representing a personal spike for a user of a client device, the personal spike comprising an instance of personal event data that deviates from a baseline of personal event data determined for the user;

perform operations to communicate with one or more computer systems over the network to collect contextual data related to the personal event data; and,

using the scenario modeling data, contextual data and the personal event data identifying the at least one personal spike:

determine and provide likely personal event scenarios consistent with the contextual data and the personal event data.

2 . The system of claim 1 wherein the personal spike deviates at least a threshold amount from the baseline of personal event data.

3 . The system of claim 1 wherein the contextual data comprises one or more of: emotion characterization data; personal spike time of occurrence data; user browsing history data; user calendar data; user messaging data comprising email, text, voice, and/or social media data for communications sent or received by the user; user positional data comprising location based services data, traffic/infrastructure data, utility service data comprising 911/emergency services dispatch data, Internet of Things (IoT) data; proximity social trend/feed data comprising social media data originated by friends/family or other person sharing a proximity relationship to the user; associated transaction behaviour data; and general information comprising news, weather, sports, business and arts/entertainment information.

4 . The system of claim 1 , wherein the at least one processor being further configured to select from among the contextual data collected using at least one relationship.

5 . The system of claim 4 wherein the relationship is a time relationship associated with a time of occurrence for the personal spike.

6 . The system of claim 4 wherein each of the personal event scenarios are associated with a respective time window associated with a time of occurrence of the personal spike and wherein the step of using for a particular personal event scenario is responsive to the time window to determine which contextual data to evaluate for the particular personal event scenario.

7 . The system of claim 6 wherein the personal event scenarios are grouped by like time windows and evaluated in order beginning with the shortest time window.

8 . The system of claim 1 , wherein the at least one processor being further configured to, for each of the likely personal event scenarios, determine a likelihood that a respective likely personal event scenario is correctly predicted; and provide the likely personal event scenarios in association with the likelihood.

9 . The system of claim 1 , wherein the at least one processor being further configured to:

perform operations to communicate with the one or more computer systems over the network to receive feedback in respect of the occurrence of the likely personal event scenario; and

use the feedback to maintain the scenario modeling data.

10 . A computer-implemented method, comprising:

maintaining, by at least one processor, scenario modeling data related to a plurality of personal event scenarios;

performing, by the at least one processor, operations to communicate with one or more computer systems over the network to receive personal event data representing a personal spike for a user of a client device, the personal spike comprising an instance of personal event data that deviates from a baseline of personal event data determined for the user;

performing, by the at least one processor, operations to communicate with one or more computer systems over the network to collect contextual data related to the personal event data; and,

using, by the at least one processor, the scenario modeling data, contextual data and the personal event data identifying the at least one personal spike to determine and provide likely personal event scenarios consistent with the contextual data and the personal event data.

11 . The method of claim 10 wherein the personal spike deviates at least a threshold amount from the baseline of personal event data.

12 . The method of claim 10 wherein the contextual data comprises one or more of: emotion characterization data; personal spike time of occurrence data; user browsing history data; user calendar data; user messaging data comprising email, text, voice, and/or social media data for communications sent or received by the user; user positional data comprising location based services data, traffic/infrastructure data, utility service data comprising 911/emergency services dispatch data, Internet of Things (IoT) data; proximity social trend/feed data comprising social media data originated by friends/family or other person sharing a proximity relationship to the user; associated transaction behaviour data; and general information comprising news, weather, sports, business and arts/entertainment information.

13 . The method of claim 10 comprising selecting, by the at least one processor, from among the contextual data collected using a time relationship associated with a time of occurrence for the personal spike.

14 . The method of claim 13 wherein each of the personal event scenarios are associated with a respective time window associated with a time of occurrence of the personal spike and wherein the step of using for a particular personal event scenario is responsive to the time window to determine which contextual data to evaluate for the particular personal event scenario.

15 . The method of claim 14 wherein the personal event scenarios are grouped by like time windows and evaluated in order beginning with the shortest time window.

16 . The method of claim 10 comprising, for each of the likely personal event scenarios, determining, by the at least one processor, a likelihood that a respective likely personal event scenario is correctly predicted; and providing the likely personal event scenarios in association with the likelihood.

17 . The method of claim 10 comprising performing, by the at least one processor, operations to communicate with one or more computer systems over the network to collect contextual data related to the personal event data.

18 . The method of claim 10 , comprising:

performing operations, by the at least one processor, to communicate with the one or more computer systems over the network to receive feedback in respect of the occurrence of the likely personal event scenario; and

using, by the at least one processor, the feedback to maintain the scenario modeling data.

19 . A system comprising:

a storage device; and

at least one processor coupled to the storage device, the storage device storing software instructions for controlling the at least one processor when executed by the at least one processor, the at least one processor being operative with the software instructions and being configured to:

perform operations to communicate with one or more first devices over a network to receive instances of personal event data for a user of a client device;

perform operations to communicate with one or more second devices over a network to receive contextual data for the user;

establish and maintain a baseline of personal event data for the user using the contextual data and instances of personal event data; and

identify a personal spike experienced from one or more instances of personal event data that deviate from the baseline.

20 . The system of claim 19 wherein the at least one processor is further configured to perform operations to communicate to the personal spike to a personal event scenario determination computer system.