Categorization based on user questionnaire

• US 10,013,492 B1
• Filed: 09/24/2010
• Issued: 07/03/2018
• Est. Priority Date: 09/24/2010
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Petts, James C., Xi, Yong, Grit, Laura Ellen, Minter, Samuel A., Fowler, Lindsey Christina, Harding, Dennis, Dykstra, Aaron James, Ionkov, George
• Primary Examiner(s): Perveen, Rehana
• Assistant Examiner(s): Wong, Huen
• Application Number:
  US12/890,445
• Time in Patent Office: 2,839 Days
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G09B 7/00 Electrically-operated teaching apparatus or devices working with questions and answers mechanically operated G09B3/00; computing arrangements G06F
• CPC Class Codes: G09B 7/02 of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student

Abstract

A customized questionnaire is generated for a content item, such as an eBook, audio file, video file, and so on. Upon an occurrence of predetermined event, the user is presented with the customized questionnaire soliciting responses to questions and/or rating evaluations relating to the content item. The responses may include reviews, ratings, recommendations of similar items, discussion topics, and other things. Information from the responses may be collected and associated with the content item to build a user-driven index.

Claims

1. A computer-implemented method comprising:

under control of one or more computer systems configured with executable instructions,

receiving an indication of a user interaction, via a user device, with an electronic book;

identifying, from a user profile, an association between a genre of electronic books and content access event (CAE) data, the CAE data including at least one of a particular time of day or a particular location;

determining, based at least in part on the indication, an occurrence of an event that is associated with at least a portion of the CAE data;

determining a rate of abandonment of electronic books associated with an ambient light intensity that is equal to or below a threshold value;

determining, based at least partly on the indication, that a current ambient light intensity received by the user device is at or below the threshold value;

generating a customized questionnaire associated with the electronic book that includes at least one question based at least in part on the genre of electronic books, the at least one question including a question associated with an abandonment of the electronic book;

sending the customized questionnaire to the user device upon an occurrence of a predetermined event to solicit a response to the at least one question;

receiving the response from the user device;

associating the response with the electronic book to build or update a user-driven index of a catalog; and

generating a different customized questionnaire for the electronic book, the different customized questionnaire including at least one different question based at least in part on the response.

2. The computer-implemented method of claim 1, further comprising:

causing display of a user interface on the user device, the user interface including one or more of free text user input, menus, list boxes, check boxes, radio buttons, or sliders to receive the response.

3. The computer-implemented method of claim 1, further comprising:

detecting an expiration of an allotted amount of time after a commencement of the user interaction, and

wherein the predetermined event is based at least at least in part on the expiration of the allotted amount of time.

4. The computer-implemented method of claim 1, further comprising:

detecting that the electronic book is being associated with at least one other electronic book in a collection of electronic books on the user device, and

wherein the user interaction is based at least in part on detecting that the electronic book is being associated.

5. The computer-implemented method of claim 1, wherein the indication of the user interaction is a first indication, and further comprising:

receiving a second indication, via the user device, of an annotation to be associated with a portion of the electronic book, and

wherein the customized questionnaire includes an additional question that solicits a recommendation for similar items based in part on the annotation associated with the portion of the electronic book.

6. The computer-implemented method of claim 1, further comprising:

causing display of at least one additional question within the customized questionnaire that solicits information regarding a category of the electronic book, a subject of the electronic book, a style of the electronic book, a format of the electronic book, or a language of the electronic book.

7. The computer-implemented method of claim 1, further comprising:

causing display of at least one additional question that is associated with assessing a reading level of the electronic book.

8. The computer-implemented method of claim 1, further comprising weighting the response based in part on a characteristic of the user profile associated with the user device.

9. The computer-implemented method of claim 8, further comprising:

identifying, from the user profile, previous responses to other customized questionnaires, and

wherein the characteristic is based at least in part on the previous responses.

10. The computer-implemented method of claim 1, further comprising providing an incentive to provide the response to the customized questionnaire.

11. The computer-implemented method of claim 1, further comprising generating a recommendation based at least in part on the user-driven index.

24. The computer-implemented method of claim 1, wherein the user device includes an ambient light sensor that measures the current ambient light intensity.

25. The computer-implemented method of claim 1, further comprising:

generating a recommendation that includes at least one or more services based at least in part on the electronic book and the response.

26. The computer-implemented method of claim 1, wherein the user device includes one or more accelerometers, and further comprising:

determining, based at least partly on the indication, that a motion of the user device corresponds to walking, and

wherein the different customized questionnaire includes a recommendation for activities associated with walking.

27. The computer-implemented method of claim 1, wherein the indication of the user interaction is a first indication, and further comprising:

receiving, via the user device, a second indication of an annotation to be associated with a portion of the electronic book, and

wherein the customized questionnaire includes at least one question that is associated with the portion of the electronic book.

28. The computer-implemented method of claim 7, further comprising:

assessing the reading level of the electronic book based at least in part on the response; and

causing display of a recommendation of additional electronic content items based at least in part on the reading level.

12. A computer-implemented method comprising:

under control of one or more computer systems configured with executable instructions,

receiving, from a user device, an indication of a user interaction, the user interaction including a purchase of a content item of a plurality of content items;

determining a rate of abandonment of content items associated with an ambient light intensity that is equal to or below a threshold value;

determining, based at least partly on the indication, that a current ambient light intensity received by the user device is at or below the threshold value;

generating a customized questionnaire for the content item of the plurality of content items;

causing display of the customized questionnaire on the user device based at least in part on the indication, the customized questionnaire to solicit a response to at least one question that is associated with an abandonment of the content item;

receiving, via the user device, the response;

associating the response with the content item to build or update a user-driven index comprising the plurality of content items; and

generating a different customized questionnaire for the content item that includes at least one different question based at least in part on the response, and a recommendation for at least one activity.

13. The computer-implemented method of claim 12, further comprising:

causing display of at least one additional question within the customized questionnaire that solicits a request for items that are identified as similar to at least one of the plurality of content items.

14. The computer-implemented method of claim 12, further comprising:

causing display of at least one additional question that assesses an education level or reading level commensurate with at least one of the plurality of content items.

15. The computer-implemented method of claim 12, further comprising:

detecting an occurrence of a predetermined event that includes at least one of a conclusion of a page of a content item, a conclusion of a chapter or a conclusion of another predefined section of the content item, an insertion of an annotation into the content item, or an expiration of an allotted amount of time; and

wherein causing display of the customized questionnaire on the user device is further based at least in part on the occurrence of the predetermined event.

16. The computer-implemented method of claim 12, further comprising generating a recommendation based at least in part on the user-driven index.

29. The computer-implemented method of claim 12, further comprising:

determining a credibility score of a user associated with the user device, the credibility score based at least in part on at least one of a measurement of user interaction with the content item or a qualification associated with the user as an expert of subject matter associated with the content item; and

determining a review value based at least in part on the credibility score,

wherein generating the at least one different question is further based at least in part on the review value being greater than a predetermined threshold.

17. A device comprising:

one or more processors;

memory accessible by the one or more processors; and

operational logic stored in the memory and executable on the one or more processors to perform actions comprising;

causing, via a user interface, display of a portion of an electronic content item;

detecting a user interaction with the electronic content item;

determining a rate of abandonment of content items associated with an ambient light intensity that is equal to or below a threshold value;

determining, based at least partly on the indication, that a current ambient light intensity received by the device is at or below the threshold value;

causing, via the user interface, display of a customized questionnaire to solicit a response to at least one question based at least in part on the electronic content item, the at least one question being associated with an abandonment of the electronic content item;

receiving the response;

transmitting the response for incorporation to a user-driven index;

and

causing, via the user interface, display of a recommendation for at least one activity associated with the response.

18. The device of claim 17, wherein the portion of the electronic content item comprises one or more of pages of the electronic content item, chapters of the electronic content item, episodes of the electronic content item, tracks of the electronic content item, or scenes of the electronic content item.

19. The device of claim 17, wherein the electronic content item comprises one or more of books, magazines, periodicals, photographs, audio, video, or music.

20. The device of claim 17, wherein the operational logic is further executable by the one or more processors to perform actions comprising:

detecting an occurrence of one or more of a conclusion of a page, chapter, episode, track, scene, or other predefined section of the electronic content item, or expiration of an allotted amount of time, and

detecting a motion of the device at least partly after detecting the occurrence.

21. The device of claim 17, wherein the operational logic is further executable by the one or more processors to perform actions comprising:

detecting an occurrence of a plurality of electronic content items being organized on the device, and

detecting a motion of the device at least partly after detecting the occurrence.

22. The device of claim 17, wherein the at least one question solicits a recommendation for similar items based at least in part on the electronic content item.

23. The device of claim 17, wherein the at least one question solicits information comprising one or more of category, subject, genre, style, format, or language of the electronic content item.

30. The device of claim 17, wherein the operational logic is further executable by the one or more processors to perform actions comprising:

determining that an annotation is to be associated with a portion of the electronic content item, based at least in part on detecting the user interaction with the electronic content item, and

wherein the at least one question of the customized questionnaire is further based at least in part on the annotation.

31. The device of claim 17, wherein the operational logic is further executable by the one or more processors to perform actions comprising:

detecting an occurrence of a predetermined event associated with the user interaction with the electronic content item, the predetermined event occurring after a purchase of the electronic content item, and

wherein causing display of the customized questionnaire is further based at least in part on the occurrence of the predetermined event.

32. The device of claim 17, wherein the electronic content item is a first electronic content item, the response is a first response, the customized questionnaire is a first customized questionnaire, and wherein the operational logic is further executable by the one or more processors to perform actions comprising:

presenting a portion of a second electronic content item for consumption, based at least in part on receiving the first response; and

presenting a second customized questionnaire that includes at least one second question based at least in part on the second electronic content item and the first response.

33. The device of claim 17, wherein the recommendation is a first recommendation, and wherein the operational logic is further executable by the one or more processors to perform actions comprising:

presenting a second recommendation of an additional electronic content item that is similar to the electronic content item, the additional electronic content item including at least one of electronic books, periodicals, music, movies, photographs, audio files, or video files.