US 2017/0372268 A1 · CONTEXTUAL MODEL-BASED EVENT SCHEDULING

Abstract

Various techniques for performing contextual event scheduling with an event scheduling service are disclosed herein. In an example, data is processed at an event scheduling service, based on the use of a trained machine learning model that is specific to a user. This trained machine learning model is operated by the event scheduling service determine a proposed time and proposed scheduling parameters based on the contextual information, to identify a proposed event time and event scheduling parameters based on the model, the data indicating a user state, or external data. Further examples to evaluate user activity and identify schedule characteristics based on data inputs from a user's mobile computing device, wearable sensors, and external weather, traffic, or event data sources, are also disclosed.

Claims25

Dependent claims

A communication device, comprising:

processing circuitry to:
receive a request to schedule a prospective electronic communication event, wherein the prospective electronic communication event is scheduled to occur between the communication device operated by a user and another communication device operated by another user;
transmit, to an event scheduling service, contextual information related to a state of the user, wherein the contextual information indicates a state of the communication device and activity of the user;
and
receive, from the event scheduling service, a proposed time and proposed scheduling parameters for the prospective electronic communication event, wherein the event scheduling service provides the proposed time and the proposed scheduling parameters in response to processing of the contextual information;
wherein the event scheduling service uses a trained machine learning model to determine the proposed time and the proposed scheduling parameters based on the contextual information related to the state of the user.

3 more elements

At least one machine readable storage medium, comprising a plurality of instructions that, responsive to being executed with processor circuitry of a communication device, cause the communication device to perform electronic operations that:

receive a request to schedule a prospective electronic communication event, wherein the prospective electronic communication event is scheduled to occur between the communication device operated by a user and another communication device operated by another user;
transmit, to an event scheduling service, contextual information related to a state of the user, wherein the contextual information indicates a state of the communication device and activity of the user;
and
receive, from the event scheduling service, a proposed time and proposed scheduling parameters for the prospective electronic communication event, wherein the event scheduling service provides the proposed time and the proposed scheduling parameters in response to processing of the contextual information;
wherein the event scheduling service uses a trained machine learning model to determine the proposed time and the proposed scheduling parameters based on the contextual information related to the state of the user.

2 more elements

Dependencies are inferred from the claim text.

Contextual model-based event scheduling

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Contextual model-based event scheduling

Life of this patent

Abstract

Claims25