Context aware user interface

• US 10,452,410 B2
• Filed: 10/25/2016
• Issued: 10/22/2019
• Est. Priority Date: 10/25/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Arar, Raphael I., Lee, Sunhwan
• Primary Examiner(s): Paula, Cesar B
• Assistant Examiner(s): Blackwell, James H.
• Application Number:
  US15/334,185
• Publication Number:
  US 20180113586A1
• Time in Patent Office: 1,092 Days
• CPC Class Codes: G06F 3/0484 for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• CPC Class Codes: G06F 9/451 Execution arrangements for user interfaces
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

A computer-implemented method according to one embodiment includes identifying one or more historical instances of device usage, determining historical contextual data for each of the one or more historical instances of the device usage, creating an event in association with the one or more historical instances of the device usage and the historical contextual data, identifying a real-time occurrence of the event by comparing real-time contextual data to the historical contextual data, and in response to identifying the real-time occurrence of the event, adjusting one or more aspects of a user interface (UI) of the device based on the one or more historical instances of the device usage.

Claims

1. A computer-implemented method, comprising:

identifying one or more historical instances of device usage;

determining historical contextual data for each of the one or more historical instances of the device usage, the historical contextual data including;

an activity being performed by a user during each of the one or more historical instances,

a role of a user performing each of the one or more historical instances, and

an identification of one or more additional devices that communicated with the device during each of the one or more historical instances of the device usage;

creating an event in association with the one or more historical instances of the device usage and the historical contextual data;

training a classifier to identify the event by inputting the historical contextual data and an associated event identifier into a machine learning algorithm;

identifying, using the trained classifier, a real-time occurrence of the event, utilizing real-time contextual data and the historical contextual data, the real-time contextual data including current calendar information and current message information, where the trained classifier analyzes the real-time contextual data to identify the real-time occurrence of the event; and

in response to identifying the real-time occurrence of the event;

adjusting one or more aspects of a user interface (UI) of the device based on the one or more historical instances of the device usage,

determining one or more additional devices in communication with the device, and

adjusting one or more aspects of the UI of the one or more additional devices.

2. The computer-implemented method of claim 1, wherein the one or more historical instances of the device usage are identified for a single user or for a predetermined group of users.

3. The computer-implemented method of claim 1, wherein the historical contextual data further includes a time each of the one or more historical instances of the device usage occurred and a location where each of the one or more historical instances of the device usage occurred.

4. The computer-implemented method of claim 1, wherein the historical contextual data further includes an identification of external data associated with the one or more historical instances of the device usage.

5. The computer-implemented method of claim 1, wherein creating the event includes associating an event identifier of the event with the one or more historical instances of the device usage and the historical contextual data.

6. The computer-implemented method of claim 1, wherein the real-time contextual data includes contextual data identified by monitoring one or more aspects of a user'"'"'s real-time device usage.

7. The computer-implemented method of claim 1, wherein adjusting the one or more aspects of the UI of the device includes changing an order of one or more applications displayed using the UI.

8. The computer-implemented method of claim 1, wherein the historical contextual data is stored at a cloud computing environment and is compared to the real-time contextual data received at the cloud computing environment.

9. The computer-implemented method of claim 1, wherein the historical contextual data further includes external data associated with the one or more historical instances of the device usage, including data stored within a calendar application and a messaging application.

10. The computer-implemented method of claim 1, wherein the one or more historical instances of the device usage are identified for a predetermined group of users.

11. A computer program product for implementing a context aware user interface (UI), the computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a processor to cause the processor to perform a method comprising:

identifying one or more historical instances of device usage, utilizing the processor;

determining historical contextual data for each of the one or more historical instances of the device usage, utilizing the processor, the historical contextual data including;

an activity being performed by a user during each of the one or more historical instances,

a role of a user performing each of the one or more historical instances, and

an identification of one or more additional devices that communicated with the device during each of the one or more historical instances of the device usage;

creating an event in association with the one or more historical instances of the device usage and the historical contextual data, utilizing the processor;

training a classifier to identify the event by inputting the historical contextual data and an associated event identifier into a machine learning algorithm, utilizing the processor;

identifying, using the trained classifier, a real-time occurrence of the event, utilizing the processor and real-time contextual data and the historical contextual data, the real-time contextual data including current calendar information and current message information, where the trained classifier analyzes the real-time contextual data to identify the real-time occurrence of the event; and

in response to identifying the real-time occurrence of the event;

adjusting, utilizing the processor, one or more aspects of a UI of the device based on the one or more historical instances of the device usage,

determining, utilizing the processor, one or more additional devices in communication with the device, and

adjusting, utilizing the processor, one or more aspects of the UI of the one or more additional devices.

12. The computer program product of claim 11, wherein the one or more historical instances of the device usage are identified for a single user or for a predetermined group of users.

13. The computer program product of claim 11, wherein the historical contextual data further includes a time each of the one or more historical instances of the device usage occurred and a location where each of the one or more historical instances of the device usage occurred.

14. A system, comprising:

a processor; and

logic integrated with the processor, executable by the processor, or integrated with and executable by the processor, the logic being configured to;

identify one or more historical instances of device usage;

determine historical contextual data for each of the one or more historical instances of the device usage, the historical contextual data including;

an activity being performed by a user during each of the one or more historical instances,

a role of a user performing each of the one or more historical instances, and

an identification of one or more additional devices that communicated with the device during each of the one or more historical instances of the device usage;

create an event in association with the one or more historical instances of the device usage and the historical contextual data;

train a classifier to identify the event by inputting the historical contextual data and an associated event identifier into a machine learning algorithm;

identify, using the trained classifier, a real-time occurrence of the event, utilizing real-time contextual data and the historical contextual data, the real-time contextual data including current calendar information and current message information, where the trained classifier analyzes the real-time contextual data to identify the real-time occurrence of the event; and

in response to identifying the real-time occurrence of the event;

adjust one or more aspects of a user interface (UI) of the device based on the one or more historical instances of the device usage,

determine one or more additional devices in communication with the device, and

adjust one or more aspects of the UI of the one or more additional devices.