Personally Impactful Changes To Events of Users

Patent metadata

Field	Value
Publication number	US-2016358065-A1
Application number	US-201514866292-A
Country	US
Kind code	A1
Filing date	Sep 25, 2015
Priority date	Jun 5, 2015
Publication date	Dec 8, 2016
Grant date	—

Abstract

In some implementations, sensors provide sensor data reflecting user activity detected by the sensors. An event analyzer generates an impact score for a change to an event associated with a user based on routine-related aspects generated from one or more user routine models associated with the user. The one or more user routine models are trained based at least in part on interaction data comprised of the sensor data. The impact score may be generated by analyzing the event attributes with respect to the routine-related aspects. The impact score is generated based on determining a difference in a level of deviation caused by the change, between one or more event attributes and routine-related aspects and based on comparing a time of the event to a reference time. The impact score can be used to determine which changes to events are important to the user.

First claim

What is claimed is:

1 . A computerized system comprising:
one or more sensors configured to provide sensor data reflecting user activity detected by the one or more sensors; an event analyzer configured generate an impact score for a change to one or more event attributes of a plurality of event attributes of an event associated with a user based on routine-related aspects generated from one or more user routine models associated with the user, the one or more user routine models trained based at least in part on interaction data comprised of the sensor data; one or more processors; and one or more computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to perform operations comprising:
receiving, using the event analyzer, a notification of the change to the one or more event attributes;
generating the impact score based on the received notification by determining a difference in a level of deviation caused by the change, between the one or more event attributes and the routine-related aspects and based on comparing a time of the event to a reference time; and
generating service content for the user based at least in part on the impact score generated for the change.

2 . The computerized system of claim 1 , wherein at least one of the routine-related aspects is a commute-related aspect generated from at least one commute-related routine model trained based on detecting a commute pattern of the user in the sensor data.

3 . The computerized system of claim 1 , wherein at least one of the routine-related aspects is a sleep-related aspect generated from at least one sleep-related routine model trained based on detecting a sleep pattern of the user in the sensor data.

4 . The computerized system of claim 1 , wherein at least one of the routine-related aspects is a location-related aspect generated from at least one location visitation-related routine model trained based on detecting a location visitation patterns of the user in the sensor data.

5 . The computerized system of claim 1 , wherein at least one of the routine-related aspects is an affinity-related aspect generated from at least one affinity-related routine model trained based on detecting affinity patterns of the user in the sensor data with respect to one or more contacts of the user.

6 . The computerized system of claim 1 , wherein the sensor data includes user activity occurring over more than one user device.

7 . The computerized system of claim 1 , wherein the one or more event attributes comprise a location of the event and a scheduled time of the event and the impact score is based, at least in part, on a probability that the user is at or near the location of the event at or near the time of the event, the probability being calculated based on at least one of the one or more user routine models that is trained based on spatial-temporal data points extracted from the sensor data.

8 . The computerized system of claim 1 , wherein the determining the difference in the level of deviation caused by the change, between the one or more event attributes and the routine-related aspects comprises:
determining a first level of deviation between the one or more event attributes and the routine-related aspects prior to the change; determining a second level of deviation between the one or more event attributes and the routine-related aspects with the change; and calculating the difference in the level of deviation using the first level of deviation and the second level of deviation.

9 . The computerized system of claim 1 , wherein the generating of the service content for the user based at least in part on the impact score generated for the change comprises automatically notifying the user of the change on a user device associated with the user.

10 . The computerized system of claim 1 , wherein the generating of the service content for the user comprises selecting from a manner of display for the service content from a plurality of predefined manners of display based on the impact score exceeding a threshold value.

11 . The computerized system of claim 1 , wherein the event corresponds to an event entry in a calendar application.

13 . A computerized method comprising:
identifying a changes of event attributes of an event stored in association with a user; receiving, routine-related aspects generated from one or more user routine models associated with the user, the one or more user routine models trained based at least in part on interaction data comprised of sensor data reflecting user activity detected by one or more sensors; applying factor metrics to the change of the event attributes to generate impact scores, each impact score corresponding to a respective factor metric and being based on a difference in a level of deviation caused by the change, between a set of the event attributes of the event and a set of routine-related aspects and based on comparing a time of the event to a reference time; selecting a subset of the factor metrics based on an analysis of the impact score of each of the factor metrics; and generating service content for the user based at least in part on the selected subset of the factor metrics.

14 . The computerized method of claim 13 , wherein a factor metric is included in the subset of the factor metrics based on having a highest impact score of the factor metrics.

15 . The computerized method of claim 13 , further comprising assigning one or more categories to the event based on the impact scores of the factor metrics, wherein at least some of the service content is predetermined based on the one or more categories assigned to the event.

16 . The computerized method of claim 13 , further comprising combining the factor metrics into an overall impact score for the event that is based on the difference in the level of deviation for each factor metric, wherein the generating service content for the user is based at least in part on the overall impact score.

17 . The computerized method of claim 13 , wherein at least one of the factor metrics is a location-visitation based factor, the level deviation being based on a distance between a location of the event from a predicted location of the user during the event.

18 . One or more computer storage devices storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising:
identifying, for each event of events stored in association with a user, a change of event attributes of the event; receiving, routine-related aspects generated from one or more user routine models associated with the user, the one or more user routine models trained based at least in part on interaction data comprised of sensor data reflecting user activity detected by one or more sensors; generating an impact score for each event of the events by analyzing the change of the event attributes of the event with respect to the routine-related aspects, the impact score being generated by determining a difference in a level of deviation caused by the change, between the event attributes and the routine-related aspects and based on comparing a time of the event to a reference time; causing service content corresponding to a subset of the events to be presented on a user device of the user based on the impact score of each event in the subset of events.

19 . The one or more computer storage devices of claim 18 , wherein a same referenc

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Gedge Nick
• Magar David
• Wascher Michael
• Zhao Richard
• Choudhary Suryakant

Classifications

• G06Q10/1093 Primary

  Calendar-based scheduling for persons or groups · CPC title

• G06N3/006 Primary

  based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO] · CPC title

• G06N5/047

  Pattern matching networks; Rete networks · CPC title

• G06N99/005

  Physics · mapped topic

• G06N20/00

  Machine learning · CPC title