Content suggestion engine

• US 9,037,578 B2
• Filed: 02/21/2013
• Issued: 05/19/2015
• Est. Priority Date: 12/03/2012
• Status: Active Grant

• Current Assignee: TheraTec, Inc. (Dynatronics Corporation)
• Original Assignee: WellClub, LLC
• Inventors: Brust, Thomas Edwin, Kennedy, Phil, Khan, Jamal, Johnson, Jay W., Waddell, Tom
• Primary Examiner(s): VO, TRUONG V
• Application Number:
  US13/772,697
• Publication Number:
  US 20140156676A1
• Time in Patent Office: 817 Days
• Field of Search: 707/726
• US Class Current: 707/726
• CPC Class Codes: G06F 16/24 Querying
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/4387 by the use of playlists
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

Systems and methods for content selection and processing in an information system are described herein. In one example, a content suggestion engine operates to select, suggest, or recommend content to human users. The selection of content may be suited to a goal or set of goals set by a human user (for example, content recommendations used to assist the human user with achieving a personal health goal). The content suggestion engine may evaluate information to help determine the appropriateness of the content suggestions, considering factors such as a psychological profile, medical conditions, lifestyle, demographics, and goals. The content may be further filtered and weighted to select a subset of content and suggested actions most relevant to the human user.

Claims

1. A method performed by a computer-implemented content suggestion engine for determining suggested content from a human activity recommendation information system, comprising:

obtaining context-sensitive content relevant to attainment of an overall selected goal that is attempted by a human subject, the context-sensitive content produced from content data stored in the human activity recommendation information system, wherein the overall selected goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities;

determining a set of conditions relevant to the attainment of the overall selected goal to establish a filter and a weight for restricting and prioritizing the context-sensitive content, the set of conditions including one or more conditions obtained from a profile of the human subject, wherein the profile tracks one or more behavior characteristics affecting the attainment of the overall selected goal by the human subject;

matching the context-sensitive content to the human subject according to the set of conditions, the matching including applying the filter to exclude content from the context-sensitive content that does not match the set of conditions;

prioritizing the context-sensitive content to the human subject according to the set of conditions, the prioritizing including applying the weight to prioritize content in the context-sensitive content that provides a greater match to the profile of the human subject; and

selecting suggested content from the filtered and prioritized context-sensitive content for presentation to the human subject.

2. The method of claim 1, further comprising:

determining timing of delivery of the suggested content, based on the set of conditions relevant to the attainment of the overall selected goal; and

electronically delivering the suggested content to the human subject according to the determined timing of delivery.

3. The method of claim 1, wherein the set of conditions relevant to the attainment of the overall selected goal includes a plurality of conditions determined from creation of the profile, the profile being created from one or more of:

input collected from the human subject, input collected from a human supporter of the human subject, a psychological model, or a coaching model; and

wherein the context-sensitive content is further restricted to activities suggested by the context-sensitive content that match attributes of the profile of the human subject.

4. The method of claim 3, wherein applying a set of conditions relevant to the context-sensitive data includes:

determining whether the context-sensitive content influences the human subject;

determining whether the human subject influences the context-sensitive content; and

based on a determination of a relationship between the context-sensitive content and the human subject, modifying the filter and the weight.

5. The method of claim 1, further comprising:

updating the context-sensitive content based on information obtained from the human subject.

6. The method of claim 5, wherein the information is obtained from the human subject by querying the human subject with one or more episodic questions.

7. The method of claim 1, wherein the suggested content indicates a suggested action for performance by the human subject, the suggested action being relevant to attainment of the overall selected goal that is pre-selected by the human subject.

8. The method of claim 1, wherein prioritizing the context-sensitive content with the weight includes prioritizing the context-sensitive content based on a plurality of weights, with respective of the plurality of weights having varying values.

9. The method of claim 1, wherein prioritizing the context-sensitive content with the weight includes prioritizing the context-sensitive content as a function of a number of times the human subject has completed one or more suggested actions associated with a behavior change attribute, the behavior change attribute relevant to one or more of:

intrinsic motivation, extrinsic motivation, individual aptitude, group factors, group power, environmental factors, or environmental power to cause behavior change.

10. The method of claim 9, wherein prioritizing the context-sensitive content with the weight further includes prioritizing the context-sensitive content associated with the behavior change attribute.

11. The method of claim 10, wherein the behavior change attribute is completed by the human subject a fewest number of times among a plurality of behavior change attributes for previous selections of context-sensitive content.

12. The method of claim 1, wherein applying a set of conditions relevant to the context-sensitive data includes matching a difficulty tag of a suggested action from the context-sensitive content to a difficulty appropriate for the human subject.

13. The method of claim 1, wherein the overall selected goal is a human behavior modification goal that is pre-selected by the human subject and that is specific to a health or wellness condition of the human subject, wherein the overall selected goal is subject to a time duration, and wherein the profile includes information that is specific to the health or wellness condition of the human subject.

14. The method of claim 13, wherein the profile includes one or more psychological characteristics, one or more demographical characteristics, and one or more lifestyle characteristics, for the human subject, in addition to the one or more behavior characteristics.

15. The method of claim 13, wherein the prioritizing of the context-sensitive content performs a ranking of the context-sensitive content based on the profile of the human subject, the profile of the human subject being adaptive over time based on a level of attainment of the overall selected goal to be achieved in a real-world setting by the human subject.

16. The method of claim 13, wherein the context-sensitive content is associated with one or more third party suggestions, the one or more third party suggestions being suggested by one or more other human supporters in a support network for the human subject, wherein the context-sensitive content associated with the one or more third party suggestions is prioritized to the human subject over other context-sensitive content.

17. An information system, comprising:

a content database to store context-sensitive content items;

a content suggestion module implemented using a processor, the content suggestion module configured for selection of suggested content from the context-sensitive content in the content database, the context-sensitive content being relevant to attainment of an overall goal that is attempted by a human subject, wherein the overall goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities, and wherein to select the suggested content, the content suggestion module is configured to;

establish a filter and a weight for narrowing the selection of context-sensitive content using a condition relevant to the attainment of the overall goal, the condition provided from a profile of the human subject, wherein the profile tracks a behavior characteristic of the human subject affecting the attainment of the overall goal by the human subject;

match the context-sensitive content to the human subject according to the condition, by applying the filter to exclude content from the context-sensitive content not satisfying the condition; and

prioritize the context-sensitive content to the human subject according to the condition, by applying the weight to produce the selection of the suggested content from the context-sensitive content having a largest prioritization for the condition and having a relevance match to the profile of the human subject; and

a content delivery module implemented using the processor, the content delivery module configured to electronically provide the selection of the suggested content based on timing, and modify content of the selection of the suggested content to increase relevance to the human subject;

wherein the selection of the suggested content includes one or more suggested actions for performance by the human subject, the one or more suggested actions relevant to the attainment of the overall goal by the human subject.

18. The information system of claim 17, wherein the weight is used to provide a preference for content having an attribute associated with an incentive of the human subject;

and

wherein the filter is used to remove content having an attribute conflicting with a restriction of the human subject.

19. The information system of claim 17, wherein the condition relevant to the attainment of the overall goal includes a plurality of conditions determined from creation of the profile, the profile created from one or more of:

input collected from the human subject, input collected from a human supporter of the human subject, a psychological model, or a coaching model; and

wherein the context-sensitive content is further filtered based on contextual impact of a plurality of activities being suggested to the human subject or to the overall goal by the suggested content.

20. The information system of claim 17, further comprising:

a supporter module configured to invoke interaction with one or more additional human supporters for attainment of the overall goal by the human subject, the one or more additional human supporters connected in a social network with the human subject, and the supporter module operably coupled to the content delivery module to deliver at least part of the suggested content to the human subject through one or more interactions between the one or more additional human supporters and the human subject.

21. The information system of claim 17, further comprising:

a conditions module configured to evaluate the condition relevant to the attainment of the overall goal to select the selected content, the condition including one or more of;

a psychological profile of the human subject;

a health condition of the human subject;

a lifestyle profile of the human subject;

a demographic profile of the human subject; and

a goal set for the human subject.

22. The information system of claim 17, further comprising:

a feedback module configured to receive feedback from the human subject about one or more suggested actions presented to the human subject from the suggested content.

23. The information system of claim 17, further comprising:

a monitoring module configured to monitor progress of the human subject toward at least one of;

the overall goal, completion of a suggested action presented to the human subject from the suggested content, or completing a playlist of suggested actions presented to the human subject from the suggested content;

wherein the monitoring module is further configured to monitor a response of the human subject to the suggested content.

24. The information system of claim 17, further comprising:

a rules database configured to maintain data for one or more rules used to filter and prioritize the context-sensitive content, and for one or more rules used to display the suggested content;

a goal information database configured to maintain data for the overall goal by the human subject and one or more actions associated with attainment of the overall goal by the human subject;

a tagging database configured to maintain data tag attributes for the context-sensitive content; and

a suggested action database configured to maintain data for selected actions provided by the suggested content, and for responses by the human subject to the suggested content;

wherein the content suggestion module is operably coupled to and accesses the rules database, the goal information database, the tagging database, and the suggested action database, in connection with the narrowing selection of the context-sensitive content.

25. A non-transitory machine readable storage medium comprising a plurality of instructions that, in response to being executed on a computing device, cause the computing device to:

retrieve, from content data stored in an human activity recommendation information system, context-sensitive content relevant to attainment of an overall goal by a human subject, wherein the overall goal is attained in connection with changes to human behavior by the human subject in a plurality of real-world activities;

establish one or more user restrictions and one or more user preferences for the context-sensitive content from a set of conditions relevant to the attainment of the overall goal, the set of conditions populated from a profile of the human subject, and the profile tracking one or more behavior characteristics of the human subject affecting the attainment of the overall goal by the human subject;

match the context-sensitive content to the human subject according to the set of conditions and the one or more restrictions, by applying the filter to exclude content from the context-sensitive content that is not compatible with the one or more restrictions and to exclude content from the context-sensitive content that is not relevant to the set of conditions;

prioritize the context-sensitive content to the human subject according to the set of conditions and the one or more preferences, by applying the one or more preferences to prefer content from the context-sensitive content that is compatible with the one or more behavior characteristics of the human subject; and

produce suggested content from the matched and prioritized context-sensitive content for presentation to the human subject.

26. The machine readable storage medium of claim 25, further comprising instructions, which when executed by the computing device, cause the computing device to:

determine timing of delivery of the suggested content; and

deliver the suggested content to the human subject according to the determined timing of delivery.

27. The machine readable storage medium of claim 25, wherein the set of conditions relevant to the context-sensitive data includes conditions determined from one or more of:

input from the human subject, input from a human supporter of a human subject, or a coaching model; and

wherein the context-sensitive data impacts or is impacted by the human subject or the environmental goal.

28. The machine readable storage medium of claim 25, wherein the instructions for applying a set of conditions relevant to the context-sensitive data include instructions, which when executed by the computing device, cause the computing device to:

determine whether the context-sensitive data influences the subject;

determine whether the human subject influences the context-sensitive data;

determine whether the human subject and the context-sensitive data are independent of each other; and

modify the filter and the weight based on a determination of a relationship between the context-sensitive data and the human subject.

29. The machine readable storage medium of claim 25, further comprising instructions, which when executed by the computing device, cause the computing device to update the context-sensitive data based on information obtained from the human subject.

30. The machine readable storage medium of claim 25, further comprising instructions, which when executed by the computing device, cause the computing device to obtain the information from the human subject by querying the human subject with episodic questions.

31. The machine readable storage medium of claim 25, wherein the instructions for prioritizing the context-sensitive content based on a weight includes instructions, which when executed by the computing device, cause the computing device to prioritize the context-sensitive content based on a plurality of weights, with respective of the plurality of weights having varying values.

32. The machine readable storage medium of claim 25, wherein the instructions for prioritizing context-sensitive content based on a weight includes instructions, which when executed by the computing device, cause the computing device to prioritize the context-sensitive as a function of the number of times the human subject has completed suggested actions in a behavior change category.

33. The machine readable storage medium of claim 25, wherein the instructions for applying a set of conditions relevant to the context-sensitive data include instructions, which when executed by the computing device, cause the computing device to match a difficulty tag of a suggested action of the plurality of suggested actions to a difficulty appropriate for the human subject.