GENERATING PERSONALIZED ROUTES FOR ONE OR MORE USERS TO IMPROVE USER WELL-BEING

• US 20180113914A1
• Filed: 10/26/2016
• Published: 04/26/2018
• Est. Priority Date: 10/26/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Mehedy, Lenin, von Cavallar, Stefan, Waywood, Nicholas I.
• Granted Patent: US 11,061,912 B2
• Time in Patent Office: Days
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G01C 21/3423 Multimodal routing, i.e. combining two or more modes of transportation, where the modes can be any of, e.g. driving, walking, cycling, public transport
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A method includes building a well-being profile for a given user based on data obtained from one or more sources associated with the given user. One or more personalized incentives for the given user are identified based on the well-being profile. A personalized route is generated based on the one or more identified personalized incentives, with the personalized route being designed to improve a well-being of the given user. A notification is transmitted to a given client device associated with the given user over a network, with the notification causing the given client device to display the personalized route.

Claims

1. A method comprising:

building a well-being profile for the given user based on data obtained from one or more sources associated with the given user;

identifying one or more personalized incentives for the given user based on the well-being profile;

generating a personalized route based on the one or more identified personalized incentives, wherein the personalized route is designed to improve a well-being of the given user; and

transmitting a notification to a given client device associated with the given user over a network, wherein the notification causes the given client device to display the personalized route;

wherein the steps are implemented by at least one processing device comprising a processor operatively coupled to memory.

2. The method of claim 1, wherein building the user model further comprises obtaining social media data from at least one social media network associated with the given user.

3. The method of claim 2, wherein the social media data comprises social media activity comprising one or more of timestamp data, geotag data and text data.

4. The method of claim 1, wherein building the user model further comprises obtaining sensor data via one or more devices.

5. The method of claim 4, wherein the one or more devices comprise one or more wearable devices.

6. The method of claim 1, wherein building the user model further comprises obtaining location data associated with the user.

7. The method of claim 1, wherein building the user model further comprises obtaining communication service data.

8. The method of claim 1, wherein building the user model comprises creating a graph network of actions of the given user and other ones of the plurality of users based on data obtained from mining the one or more social networks of the given user.

9. The method of claim 8, wherein identifying the patterns of personal attributes for the given user comprises traversing the graph network using one or more graph algorithms.

10. The method of claim 1, wherein identifying the patterns of personal attributes for the given user comprises utilizing cognitive learning algorithms.

11. The method of claim 1, further comprising registering the given client device with a server to receive personalized routing for the given user.

12. A computer program product comprising a computer readable storage medium for storing computer readable program code which, when executed, causes a computer to perform the steps of:

building a well-being profile for the given user based on data obtained from one or more sources associated with the given user;

identifying one or more personalized incentives for the given user based on the well-being profile;

generating a personalized route based on the one or more identified personalized incentives, wherein the personalized route is designed to improve a well-being of the given user; and

transmitting a notification to a given client device associated with the given user over a network, wherein the notification causes the given client device to display the personalized route.

13. An apparatus comprising:

a processing device comprising a processor coupled to a memory;

the processing device being configured to;

build a well-being profile for a given user based on data obtained from one or more sources associated with the given user;

identify one or more personalized incentives for the given user based on the well-being profile;

generate a personalized route based on the one or more identified personalized incentives, wherein the personalized route is designed to improve a well-being of the given user; and

transmit a notification to a given client device associated with the given user over a network, wherein the notification causes the given client device to display the personalized route.

14. The apparatus of claim 13, wherein the building of the user model further comprises an obtaining of data selected from the group consisting of:

social media data from at least one social media network associated with the given user, sensor data via one or more devices, location data associated with the user, and communication service data.

15. The apparatus of claim 14, wherein the one or more devices comprise one or more wearable devices.

16. The apparatus of claim 13, wherein building the user model comprises creating a graph network of actions of the given user and other ones of the plurality of users based on data obtained from mining the one or more social networks of the given user.

17. The apparatus of claim 13, wherein the identification of the patterns of personal attributes for the given user comprises a traversal of the graph network using one or more graph algorithms.

18. The apparatus of claim 13, wherein the identification of the patterns of personal attributes for the given user comprises a utilization of cognitive learning algorithms.

19. The apparatus of claim 13, wherein the processing device implements a cloud-based server.

20. The apparatus of claim 19, wherein the given client device comprises a mobile client device and the cloud-based server is configured to communicate with the mobile client device over one or more wireless channels.