Distributed relationship reasoning engine for generating hypothesis about relations between aspects of objects in response to an inquiry
US-10762433-B2 · Sep 1, 2020 · US
US11900276B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11900276-B2 |
| Application number | US-202016938854-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 24, 2020 |
| Priority date | Mar 22, 2011 |
| Publication date | Feb 13, 2024 |
| Grant date | Feb 13, 2024 |
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A reasoning engine is disclosed. Contemplated reasoning engines acquire data relating to one or more aspects of various environments. Inference engines within the reasoning engines review the acquire data, historical or current, to generate one or more hypotheses about how the aspects of the environments might be correlated, if at all. The reasoning engine can attempt to validate the hypotheses through controlling acquisition of the environment data.
Opening claim text (preview).
What is claimed is: 1. A computer implemented method of providing recommendations based on observed objects in an environment, the method comprising: receiving, via a data interface, sensor data representing a digital representation of a scene of the environment having at least one object; recognizing target objects from aspects of the at least one object represented in the digital representation and based on data features derived from the digital representation, the recognized target objects having object attributes; selecting at least one reasoning rule set as a function of the aspects of the at least one object represented in the digital representation and the object attributes of the recognized target objects, wherein the at least one reasoning rule set is selected based on mapping at least the object attributes of the recognized target objects to concept maps comprising pointers to types of reasoning; generating at least one hypothesis according to the selected at least one reasoning rule set, the at least one hypothesis representing a correlation among the recognized target objects; and presenting to a user, via a user interface, a recommendation relating to the recognized target objects and derived at least in part from the at least one hypothesis. 2. The method of claim 1 , wherein the digital representation comprises image data. 3. The method of claim 1 , wherein at least one of the recognized target objects comprises a real-world object. 4. The method of claim 1 , wherein at least one of the recognized target objects comprises at least one virtual object. 5. The method of claim 4 , wherein the at least one virtual object comprises an augmented reality object. 6. The method of claim 1 , wherein the digital representation of the scene represents a real-world environment. 7. The method of claim 1 , wherein the digital representation of the scene represents a virtual environment. 8. The method of claim 1 , wherein the digital representation of the scene represents an augmented reality environment. 9. The method of claim 1 , wherein receiving the sensor data includes receiving the digital representation via a media outlet operating as the data interface. 10. The method of claim 1 , further comprising instantiating a new target object from data derived from the digital representation of the scene. 11. The method of claim 10 , further comprising provision the new target object with new object attributes derived from the digital representation. 12. The method of claim 1 , further comprising validating the at least one hypothesis. 13. The method of claim 12 , wherein the validating the at least one hypothesis includes generating a validation plan. 14. The method of claim 13 , wherein the recommendation is at least part of the validation plan. 15. The method of claim 13 , further comprising injecting data back to at least one user via the data interface according to the validation plan. 16. The method of claim 15 , wherein the injected data comprises at least one of the following: a survey, a command, a direct query, an alteration to a game, and a validation request. 17. The method of claim 1 , wherein receiving the sensor data includes receiving an inquiry relating to a possible relationship among the recognized target objects and based on the digital representation. 18. The method of claim 1 , further comprising relating the recognized target objects to each other based on proximity in the digital representation. 19. The method of claim 18 , wherein the proximity is determined based on at least one of the following object attributes: a time and a location. 20. The method of claim 1 , wherein at least one of the recognized target objects includes at least one of the following: a movie and a game. 21. The method of claim 1 , further comprising assigning a merit score to the at least one hypothesis based on validity of the at least one hypothesis. 22. The method of claim 1 , further comprising presenting a reasoning behind the at least one hypothesis. 23. A computer-based reasoning system for providing recommendations based on observed objects in an environment, comprising: at least one computer-readable memory storing determination software instructions and alert software instructions; at least one processor coupled with the at least one computer-readable memory and that, upon execution of the determination software instructions, operates as a data interface to receive sensor data representing a digital representation of a scene of the environment having at least one object; at least one processor coupled with the at least one computer-readable memory and that, upon execution of the determination software instructions, operates as at least one inference engine coupled within the data interface, to: recognize target objects from aspects of the at least one object represented in the digital representation and based on data features derived from the digital representation, the recognized target objects having object attributes; select at least one reasoning rule set as a function of the aspects of the at least one object represented in the digital representation and the object attributes of the recognized target objects, wherein the at least one reasoning rule set is selected based on mapping at least the object attributes of the recognized target objects to concept maps comprising pointers to types of reasoning; generate at least one hypothesis according to the selected at least one reasoning rule set, the at least one hypothesis representing a correlation among the recognized target objects; and at least one processor coupled with the at least one computer-readable memory and that, upon execution of the determination software instructions, operates as a user interface to present to a user a recommendation relating to the recognized target objects and derived at least in part from the at least one hypothesis. 24. A computer program product embedded in a non-transitory computer readable medium comprising instructions executable by a computer processor to perform operations comprising: receiving, via a data interface, sensor data representing a digital representation of a scene of the environment having at least one object; recognizing target objects from aspects of the at least one object represented in the digital representation and based on data features derived from the digital representation, the recognized target objects having object attributes; selecting at least one reasoning rule set as a function of the aspects of the at least one object represented in the digital representation and the object attributes of the recognized target objects, wherein the at least one reasoning rule set is selected based on mapping at least the object attributes of the recognized target objects to concept maps comprising pointers to types of reasoning; generating at least one hypothesis according to the selected at least one reasoning rule set, the at least one hypothesis representing a correlation among the recognized target objects; and presenting to a user, via a user interface, a recommendation relating to the recognized target objects and derived at least in part from the at least one hypothesis.
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