Back to results
US 11,593,741 B2Granted
Personal data fusion
AssigneeModuleq, Inc.
InventorsDavid James Brunner, Peter Taraba, Anupriya Ankolekar
Life of this patent
Estimating the term…
Abstract
The present disclosure contemplates a variety of improved methods and systems for providing professionals and organizations tools to improve productivity and efficiency. The present disclosure includes a process for discovering and validating entity objectives. In an embodiment, the method and system receive communications from multiple data sources (e.g., email, calendar, contacts), find correlations between the communications, identify communications that appear to be important to a user, and provide relevant resources.
Claims20
A method comprising:
- capturing, by a computer system, electronic communication data associated with an entity within an enterprise, the electronic communication data extracted from electronic communications transmitted over a network between a computing device associated with the entity and each of a plurality of other computing devices;
- determining, by the computer system, an objective of the entity based on the electronic communication data;
- applying, by the computer system, a trained machine learning model to features associated with relationships between the electronic communications in the captured electronic communication data, wherein the trained machine learning model when applied to the features is configured to output an estimated degree of importance of the objective to the entity;
- in response to the estimated degree of importance to the entity satisfying a specified criterion, by the computer system, querying a data repository associated with the enterprise using the objective to identify an electronic resource for assisting the entity in achieving the objective;
- sending, by the computer system, an indication of the electronic resource to the computing device associated with the entity for output to the entity;
- determining, based on feedback received from the entity regarding relevance of the electronic resource to the entity, an assessed degree of importance of the objective to the entity;
- and
- updating, by the computer system, the trained machine learning model based on a difference between the estimated degree of importance of the objective to the entity and the assessed degree of importance of the objective to the entity.
5 more elements
A system comprising:
- a processor;
- and
- a memory storing instructions, execution of which by the processor causes the system to:
- capture electronic communication data associated with an entity within an enterprise, the electronic communication data extracted from electronic communications transmitted over a network between a computing device associated with the entity and each of a plurality of other computing devices;
- determine an objective of the entity based on the electronic communication data;
- apply a trained machine learning model to features associated with relationships between the electronic communications in the captured electronic communication data, wherein the trained machine learning model when applied to the features is configured to output an estimated degree of importance of the objective to the entity;
- in response to the estimated degree of importance to the entity satisfying a specified criterion, query a data repository associated with the enterprise using the objective to identify an electronic resource for assisting the entity in achieving the objective;
- send an indication of the electronic resource to the computing device associated with the entity for output to the entity;
- determine, based on feedback received from the entity regarding relevance of the electronic resource to the entity, an assessed degree of importance of the objective to the entity;
- and
- update the trained machine learning model based on a difference between the estimated degree of importance of the objective to the entity and the assessed degree of importance of the objective to the entity.
8 more elements
A computer program product including non-transitory computer-readable media storing computer program instructions, execution of which by a processor causes the processing system to perform operations comprising:
- capturing electronic communication data associated with an entity within an enterprise, the electronic communication data extracted from electronic communications transmitted over a network between a computing device associated with the entity and each of a plurality of other computing devices;
- determining an objective of the entity based on the electronic communication data;
- applying a trained machine learning model to features associated with relationships between the electronic communications in the captured electronic communication data, wherein the trained machine learning model when applied to the features is configured to output an estimated degree of importance of the objective to the entity;
- in response to the estimated degree of importance to the entity satisfying a specified criterion, querying a data repository associated with the enterprise using the objective to identify an electronic resource for assisting the entity in achieving the objective;
- sending an indication of the electronic resource to the computing device associated with the entity for output to the entity;
- determining, based on feedback received from the entity regarding relevance of the electronic resource to the entity, an assessed degree of importance of the objective to the entity;
- and
- updating the trained machine learning model based on a difference between the estimated degree of importance of the objective to the entity and the assessed degree of importance of the objective to the entity.
5 more elements
Dependencies are inferred from the claim text.