System and methods for discovering and managing knowledge, insights, and intelligence using a context engine having the ability to provide a logical semantic understanding of event circumstances

• US 10,467,065 B2
• Filed: 09/13/2017
• Issued: 11/05/2019
• Est. Priority Date: 09/13/2017
• Status: Active Grant

• Current Assignee: Apiri, LLC
• Original Assignee: Apiri, LLC
• Inventors: Ross, Edward Penstone, Ross, David Marion Giles
• Primary Examiner(s): Anya, Charles E
• Application Number:
  US15/703,107
• Publication Number:
  US 20190079810A1
• Time in Patent Office: 783 Days
• CPC Class Codes: G06F 16/288 Entity relationship models
• CPC Class Codes: G06F 9/542 Event management; Broadcasting; Multicasting; Notifications
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

The disclosure relates to a context engine that can be used to identify, align, associate, validate, anticipate, and analyze new knowledge, insights and intelligence from large amounts of digital data. The essential foundation of knowledge about events is the clear and specific definition and understanding of the circumstances of those events. The present disclosure integrates modern technological capabilities including relational database structures and processing algorithms with an underlying semantic foundation to provide the opportunity for contextual understanding, analysis and insight. In various embodiments, the context engine may be based on “Five W” event circumstances, including “Who”, “Where”, “When”, “What”, and “Why” circumstances that provide a logical semantic foundation for knowledge and understanding about modeled events, enabling users to associate those circumstances with existing information. Accordingly, the context engine may provide a substantive, intuitive, scalable, and searchable layer of context to the universe of available data and information.

Claims

1. A method for identifying and documenting events based on logical semantic circumstance dimensions, comprising:

receiving, at a context engine having one or more processors, data that defines at least a first event and multiple additional events;

storing, in a database coupled to the context engine, the received data that defines at least the first event and the multiple additional events according to a circumstance-event relationship model, wherein the circumstance-event relationship model defines relationships among individual event circumstances associated with the first event and among different combinations of the individual event circumstances in multiple dimensions, wherein the circumstance-event relationship model uniquely identifies at least one of the first event or the multiple additional events according to a concatenated aggregation of unique values for actor, location, time, action, and motivation circumstances;

determining, at the context engine, a relationship between the first event and one or more of the multiple additional events based on an evaluation of a selected one of the individual event circumstances and one or more other event circumstances associated with the first event, and different combinations of the one or more other event circumstances associated with the first event in the multiple dimensions; and

providing, by the context engine, one or more analytic tools to analyze the relationship between the first event and the one or more of the multiple additional events.

2. The method recited in claim 1, wherein the individual event circumstances include at least an actor associated with an event, a time when the event occurred, a place where the event occurred, an action representing what occurred in the event, and a motivation indicating why the event occurred.

3. The method recited in claim 1, further comprising:

displaying, on a user interface coupled to the context engine, an event construct representing circumstances of the one or more of the multiple additional events that are associated with the first event in the multiple dimensions.

4. The method recited in claim 3, wherein the displayed event construct comprises a tetrahedron having four points that respectively represent four different circumstances associated with a particular event and a sphere merged with the tetrahedron to represent a fifth circumstance associated with the particular event.

5. The method recited in claim 1, further comprising:

determining, at the context engine, a relationship between a first value for a selected one of the individual event circumstances and a second value for the selected one of the individual event circumstances, wherein the relationship between the first value and the second value for the selected one of the individual event circumstances is one of an equivalent, nested, or proximity relationship.

6. The method recited in claim 1, wherein the relationship between the first event and the one or more of the multiple additional events is determined based on a dimensional weighting applied to multiple scores that represent an affinity between the individual event circumstances associated with the first event and the one or more of the multiple additional events in the multiple dimensions other than one of the multiple dimensions selected for investigation.

7. The method recited in claim 1, further comprising:

assigning a veracity score to the first event, wherein the assigned veracity score indicates a degree to which the first event is considered truthful.

8. The method recited in claim 7, wherein the veracity score assigned to the first event has a zero value in response to the one or more of the multiple additional events containing an actor circumstance and a time circumstance that match the first event and a high confidence place circumstance that differs from the first event.

9. The method recited in claim 7, wherein the veracity score assigned to the first event has a non-zero value based on a consistency among circumstances associated with different events involving an actor associated with the first event in response to determining that no other known events contain an actor circumstance and a time circumstance that match the first event and a high confidence place circumstance that differs from the first event.

10. The method recited in claim 1, further comprising:

identifying one or more potential values for one of the individual event circumstances associated with the first event in response to the received data partially defining circumstances associated with the first event, wherein the one or more potential values are determined based on a veracity score indicating a degree to which one or more events that match the partially defined circumstances are considered truthful.

11. The method recited in claim 1, wherein the data that defines the first event is received via one or more crowd sourcing and batch collection methods.

12. The method recited in claim 1, wherein the data that defines the first event is received via a circumstance and event entry user interface.

13. A system for identifying and documenting events based on logical semantic circumstance dimensions, comprising:

an input device configured to receive data that defines at least a first event and multiple additional events;

a database configured to store the received data that defines at least the first event and the multiple additional events according to a circumstance-event relationship model that defines relationships among individual event circumstances and among different combinations of the individual event circumstances in multiple dimensions, wherein the circumstance-event relationship model uniquely identifies at least one of the first event or the multiple additional events according to a concatenated aggregation of unique values for actor, location, time, action, and motivation circumstances; and

at least one processor configured to determine a relationship between the first event and one or more of the multiple additional events based on an evaluation of other event circumstances associated with the first event, and different combinations of the other event circumstances associated with the first event in the multiple dimensions and to provide one or more analytic tools to analyze the relationship between the first event and the one or more of the multiple additional events.

14. The system recited in claim 13, wherein the individual event circumstances include at least an actor associated with an event, a time when the event occurred, a place where the event occurred, an action representing what occurred in the event, and a motivation indicating why the event occurred.

15. The system recited in claim 13, further comprising a display device configured to display an event construct representing circumstances of the one or more of the multiple additional events that are associated with the first event in the multiple dimensions.

16. The system recited in claim 15, wherein the displayed construct comprises a tetrahedron having four points that respectively represent four different circumstances associated with a particular event and a sphere merged with the tetrahedron to represent a fifth circumstance associated with the particular event.

17. The system recited in claim 13, wherein the at least one processor is further configured to determine a relationship between a first value for a selected one of the individual event circumstances and a second value for the selected one of the individual event circumstances, wherein the relationship between the first value and the second value for the selected one of the individual event circumstances is one of an equivalent, nested, or proximity relationship.

18. The system recited in claim 13, wherein the relationship between the first event and the one or more of the multiple additional events is determined based on a dimensional weighting applied to multiple scores that represent an affinity between the individual event circumstances associated with the first event and the one or more of the multiple additional events in the multiple dimensions other than one of the multiple dimensions selected for investigation.

19. The system recited in claim 13, wherein the at least one processor is further configured to assign a veracity score to the first event, the assigned veracity score indicating a degree to which the first event is considered truthful.

20. The system recited in claim 19, wherein the veracity score assigned to the first event has a zero value in response to the one or more of the multiple additional events containing an actor circumstance and a time circumstance that match the first event and a high confidence place circumstance that differs from the first event.

21. The system recited in claim 19, wherein the veracity score assigned to the first event has a non-zero value based on a consistency among circumstances associated with different events involving an actor associated with the first event in response to a determination that no other known events contain an actor circumstance and a time circumstance that match the first event and a high confidence place circumstance that differs from the first event.

22. The system recited in claim 13, wherein the at least one processor is further configured to identify one or more potential values for one of the individual event circumstances associated with the first event in response to the received data partially defining circumstances associated with the first event, the one or more potential values determined based on a veracity score indicating a degree to which one or more events that match the partially defined circumstances are considered truthful.

23. The system recited in claim 13, wherein the input device is configured to receive the data that defines the first event via one or more crowd sourcing and batch collection methods.

24. The system recited in claim 13, wherein the input device is configured to receive the data that defines the first event via a circumstance and event entry user interface.

25. A non-transitory computer-readable storage medium having computer-executable instructions recorded thereon, the computer-executable instructions configured to cause a computer having at least one processor to:

receive data that defines at least a first event and multiple additional events;

store the received data that defines at least the first event and the multiple additional events in a database according to a circumstance-event relationship model, wherein the circumstance-event relationship model defines relationships among individual event circumstances and among different combinations of the individual event circumstances in multiple dimensions, wherein the circumstance-event relationship model uniquely identifies at least one of the first event or the multiple additional events according to a concatenated aggregation of unique values for actor, location, time, action, and motivation circumstances;

determine a relationship between the first event and one or more of the multiple additional events based on an evaluation of other event circumstances associated with the first event, and different combinations of the other event circumstances associated with the first event in the multiple dimensions; and

provide one or more analytic tools to analyze the relationship between the first event and the one or more of the multiple additional events.