Real-time data source and configuration identification for geospatial collaboration environments
AssigneeImmersive Wisdom, Inc.
InventorsMichael S. Appelbaum, Fred Denver Coulson, III
Life of this patent
Estimating the term…
Abstract
Systems and methods are provided for generating, in real-time, recommendations for different data elements for different virtual three-dimensional environments. As users interact with data elements presented within these virtual three-dimensional environments, these interactions and changes are processed using a machine learning algorithm in real-time to provide recommendations for new data elements that can be introduced in these virtual three-dimensional environments. Based on responses to these recommendations, the new data elements can be introduced in these virtual three-dimensional environments. Further, the machine learning algorithm is dynamically updated based on these responses.
Claims21
A computer-implemented method, comprising:
- detecting a request to create a virtual three-dimensional room, wherein the request is associated with a user, and wherein the request includes a configuration for the virtual three-dimensional room;
- processing aggregated data corresponding to user behaviors and configurations of different virtual three-dimensional rooms through a trained machine learning algorithm to identify a set of user behavior and data source trends;
- evaluating the set of user behavior and data source trends according to the configuration to generate a set of recommendations, wherein the set of recommendations corresponds to new data elements for the virtual three-dimensional room;
- providing the set of recommendations;
- receiving one or more responses to the set of recommendations, wherein the one or more responses indicate acceptance of the new data elements;
- providing element data corresponding to the new data elements, wherein when the element data is received, the element data causes a device corresponding to the user to display the new data elements within the virtual three-dimensional room according to the configuration;
- and
- dynamically updating the trained machine learning algorithm according to the set of recommendations and the one or more responses.
A system, comprising:
- one or more processors;
- and
- memory storing thereon instructions that, as a result of being executed by the one or more processors, cause the system to:
- detect a request to create a virtual three-dimensional room, wherein the request is associated with a user, and wherein the request includes a configuration for the virtual three-dimensional room;
- process aggregated data corresponding to user behaviors and configurations of different virtual three-dimensional rooms through a trained machine learning algorithm to identify a set of user behavior and data source trends;
- evaluate the set of user behavior and data source trends according to the configuration to generate a set of recommendations, wherein the set of recommendations corresponds to new data elements for the virtual three-dimensional room;
- provide the set of recommendations;
- receive one or more responses to the set of recommendations, wherein the one or more responses indicate acceptance of the new data elements;
- provide element data corresponding to the new data elements, wherein when the element data is received, the element data causes a device corresponding to the user to display the new data elements within the virtual three-dimensional room according to the configuration;
- and
- dynamically update the trained machine learning algorithm according to the set of recommendations and the one or more responses.
A non-transitory computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to:
- detect a request to create a virtual three-dimensional room, wherein the request is associated with a user, and wherein the request includes a configuration for the virtual three-dimensional room;
- process aggregated data corresponding to user behaviors and configurations of different virtual three-dimensional rooms through a trained machine learning algorithm to identify a set of user behavior and data source trends;
- evaluate the set of user behavior and data source trends according to the configuration to generate a set of recommendations, wherein the set of recommendations corresponds to new data elements for the virtual three-dimensional room;
- provide the set of recommendations;
- receive one or more responses to the set of recommendations, wherein the one or more responses indicate acceptance of the new data elements;
- provide element data corresponding to the new data elements, wherein when the element data is received, the element data causes a device corresponding to the user to display the new data elements within the virtual three-dimensional room according to the configuration;
- and
- dynamically update the trained machine learning algorithm according to the set of recommendations and the one or more responses.
Dependencies are inferred from the claim text.