IP Library Granted Patent US 10,802,849
Granted Patent B1
US 10,802,849 · App. 16/441,651 · Granted Oct 13, 2020

GUI-implemented cognitive task forecasting

Inventors: Craig M. Trim (Ventura, CA); Michael Bender (Rye Brook, NY); Martin G. Keen (Cary, NC); Jeremy R. Fox (Georgetown, TX)
Assignee: International Business Machines Corporation
G06F9/453G06N5/043G06N20/00G06Q10/063116H04L51/046H04L51/38
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Quick Facts
Patent No.
US 10,802,849
App. No.
16/441,651
Granted
Oct 13, 2020
Kind
B1
Abstract

A method, system, and computer program product for modifying a graphical user interface (GUI) according to cognitively forecasted tasks may collect a set of training data for a cognitive task managing model, where the set of training data associated with a user. The cognitive task managing model is then trained with the set of training data. The cognitive task managing model then processes a set of operational data that is associated with a user. In response to receiving a set of processed data, a task forecast is generated for the user. Based on that forecast, an optimal task for the user is determined. A set of graphical elements within the GUI are modified to notify the user of the optimal task.

Claims (34)

1. A method for modifying a graphical user interface (GUI) according to cognitively forecasted tasks, the method comprising:

collecting a set of training data for a cognitive task managing model, the set of training data associated with a user, wherein the set of training data includes a plurality of univariate time series datasets, and wherein each univariate time series dataset includes collaborative messaging data, application activity data, and scheduled activity data for the user at a particular time;

training the cognitive task managing model, using the set of training data;

processing, using the cognitive task managing model, a set of operational data associated with the user;

in response to receiving a set of processed operational data, generating a task forecast for the user;

determining, based on the task forecast, an optimal task for the user; and

modifying a set of graphical elements within the GUI to notify the user of the optimal task.

2. The method of claim 1 , wherein the cognitive task managing model employs a Micro Seasonal Autoregressive Integrated Moving Average (msARIMA).

3. The method of claim 1 , wherein collaborative messaging data includes email, text message, instant messaging, collaborative platform communications, and audio communications.

4. The method of claim 1 , wherein the application activity data includes applications associated with the user that are in use at the particular time.

5. The method of claim 1 , wherein the scheduled activity data includes calendar entries, program schedules, and historical information associated with the user at the particular time.

6. The method of claim 3 , wherein modifying a set of graphical elements within the GUI includes initiating a chat bot to remind the user of the optimal task, wherein the chat bot presents, to the user, an interactive link, via the GUI, that directs the user to a set of resources needed for the optimal task.

7. A computer program product for modifying a graphical user interface (GUI) according to cognitively forecasted tasks, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a device to cause the device to:

collect a set of training data for a cognitive task managing model, the set of training data associated with a user, wherein the set of training data includes a plurality of univariate time series datasets, and wherein each univariate time series dataset includes collaborative messaging data, application activity data, and scheduled activity data for the user at a particular time;

train the cognitive task managing model, using the set of training data;

process, using the cognitive task managing model, a set of operational data associated with the user;

in response to receiving a set of processed operational data, generate a task forecast for the user;

determine, based on the task forecast, an optimal task for the user; and

modifying a set of graphical elements within the GUI to notify the user of the optimal task.

8. The computer program product of claim 7 , wherein the cognitive task managing model employs a Micro Seasonal Autoregressive Integrated Moving Average (msARIMA).

9. The computer program product of claim 7 , wherein the collaborative messaging data includes email, text message, instant messaging, collaborative platform communications, and audio communications.

10. The computer program product of claim 7 , wherein the application activity data includes applications associated with the user that are in use at the particular time.

11. The computer program product of claim 7 , wherein the scheduled activity data includes calendar entries, program schedules, and historical information associated with the user at the particular time.

12. The computer program product of claim 9 , wherein modifying a set of graphical elements within the GUI includes initiating a chat bot to remind the user of the optimal task, wherein the chat bot presents, to the user, an interactive link, via the GUI, that directs the user to a set of resources needed for the optimal task.

13. A system for modifying a graphical user interface (GUI) according to cognitively forecasted tasks, comprising:

a memory with program instructions stored thereon; and

a processor in communication with the memory, wherein the program instructions are executable by the processor to cause the system to:

collect a set of training data for a cognitive task managing model, the set of training data associated with a user, wherein the set of training data includes a plurality of univariate time series datasets, and wherein each univariate time series dataset includes collaborative messaging data, application activity data, and scheduled activity data for the user at a particular time;

train the cognitive task managing model, using the set of training data;

process, using the cognitive task managing model, a set of operational data associated with the user;

in response to receiving a set of processed operational data, generate a task forecast for the user;

determine, based on the task forecast, an optimal task for the user; and

modifying a set of graphical elements within the GUI to notify the user of the optimal task.

14. The system of claim 13 , wherein the cognitive task managing model employs a Micro Seasonal Autoregressive Integrated Moving Average (msARIMA).

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 14, 2019
From: TRIM, CRAIG M.; BENDER, MICHAEL; KEEN, MARTIN G.; FOX, JEREMY R.
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 049471/0822 →
Cited By (2)
US 12,481,942 US 12,614,197