Characterization of Layered Documents in HTML5 Publishing

• US 20140012685A1
• Filed: 07/05/2012
• Published: 01/09/2014
• Est. Priority Date: 07/05/2012
• Status: Active Grant

• Current Assignee: Chegg Incorporated
• Original Assignee: Chegg Incorporated
• Inventors: Le Chevalier, Vincent, Geiger, Charles F., Joshi, Ashit, Eder-Pressman, Ohad, Tworetzky, Brent S., Eckenberg, Dax, Desai, Rahul Ravindra Mutalik, Wetter, Pierce Trowbridge III
• Granted Patent: US 9,489,355 B2
• Time in Patent Office: Days
• US Class Current: 705/14.73
• CPC Class Codes: G06F 40/114 Pagination
• CPC Class Codes: G06F 40/143 Markup, e.g. Standard Generalized Markup Language [SGML] or Document Type Definition [DTD]
• CPC Class Codes: G06F 40/169 Annotation, e.g. comment data or footnotes
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

An education digital reading platform provides pages of a document requested by a user, the pages including additional content layers associated with the requested content. The additional content layers including related content, user generated content, advertisement content and other services content offered by the digital reading platform. The requested content and additional content layers require processing capability on a web browser application. The amount of data associated with a page of a document may vary dramatically especially considering the additional layers of content associated with the pages. In order to permit the web browser application anticipate the processing needs associated with each page, the digital reading platform provides markers indicating a difference in processing requirements associated between two pages of a document. The markers enable the web browser request additional resources to provide a seamless user experience or enable the web browser application to request additional or fewer content layers.

Claims

1. A computer-implemented method of providing characterizations of content layers associated with a markup language document, the method comprising:

accessing deconstructed data for the markup language document, the deconstructed data comprising data structure and page information of the markup language document;

creating page markers based on the data structure and page information, the page markers characterizing the complexity of page information in terms of resources to display the page; and

providing the created markers to a web browser application requesting a page of the markup language document, the markers enabling the web browser application to manage resources based on the created markers.

2. The method of claim 1, wherein data structure and page information comprises at least one of text, font and image information associated with pages of the markup language document

3. The method of claim 1, further comprising:

receiving an identification of content related to content of pages of the markup language document;

identifying data structure and page information associated with the related content; and

creating related content markers for the pages of the markup language document based on the received identification of the related content, the markers characterizing the complexity of the related content in terms of resources to display the related content and based on the related content data structure and page information.

4. The method of claim 3, wherein the related content comprises at least one of documents, webpages, images and videos associated with content in the pages of the markup language document.

5. The method of claim 1, further comprising:

receiving user generated content associated with pages of the markup language document, the user generated content created by a user of the markup language document and including data structure and page information associated with the user generated content; and

creating user generated content markers for the pages of the markup language document based on the received user generated content, the user generated content marker characterizing the complexity of the user generated content in terms of resources to display the user generated content and based on the user generated content data structure and page information.

6. The method of claim 5, wherein the user generated content comprises at least one of notes, highlights and underlines made by users on pages of the markup language document.

7. The method of claim 1, further comprising:

receiving advertisement content associated with pages of the markup language document, the advertisement content to be displayed within pages of the markup language document and including content structure and page information associated with the advertisement content; and

creating advertisement content markers for the pages of the markup language document based on the received advertisement content, the advertisement content markers characterizing the complexity of the advertisement content in terms of resources to display the advertisements and based on the advertisement content structure and page information.

8. The method of claim 7, wherein the advertisement content comprises targeted advertisements received from an ad manifest, the ad manifest providing advertisements to be served within pages of the markup language document.

9. The method of claim 1, further comprising creating system reserved markers based on services that can be provided on a page of the document, the system reserved markers characterizing the complexity of service content that can be displayed with the markup language document, the service content providing at least one of interactive or social networking capabilities.

10. The method of claim 1, further comprising:

adding delta markers associated with each page of the markup language document, the delta markers comprising an estimated difference between page markers, related content markers, user generated content markers, advertisement content markers and system reserved markers;

calculating a difference between the added delta markers of consecutive pages of the markup language document; and

providing the calculated difference to the web browser application.

11. The method of claim 1, further comprising:

receiving performance feedback data characterizing the amount of processing power available to the web browser application responsive to receiving the marker data; and

changing content layers sent to the web browser application responsive to receiving the performance feedback data.

12. The method of claim 1, wherein the markup language document comprises an HTML5 document.

13. A computer-readable storage medium storing executable computer program instructions for providing characterizations of content layers associated with a markup language document, the computer program instructions comprising instructions for:

accessing deconstructed data for the markup language document, the deconstructed data comprising data structure and page information of the markup language document;

creating page markers based on the data structure and page information, the page markers characterizing the complexity of page information in terms of resources to display the page; and

providing the created markers to a web browser application requesting a page of the markup language document, the markers enabling the web browser application to manage resources based on the created markers.

14. The computer-readable medium of claim 13, wherein data structure and page information comprises at least one of text, font and image information associated with pages of the markup language document

15. The computer-readable medium of claim 13, further comprising instructions for:

receiving an identification of content related to content of pages of the markup language document;

identifying data structure and page information associated with the related content; and

creating related content markers for the pages of the markup language document based on the received identification of the related content, the markers characterizing the complexity of the related content in terms of resources to display the related content and based on the related content data structure and page information.

16. The computer-readable medium of claim 15, wherein the related content comprises at least one of documents, webpages, images and videos associated with content in the pages of the markup language document.

17. The computer-readable medium of claim 13, further comprising instructions for:

receiving user generated content associated with pages of the markup language document, the user generated content created by a user of the markup language document and including data structure and page information associated with the user generated content; and

creating user generated content markers for the pages of the markup language document based on the received user generated content, the user generated content marker characterizing the complexity of the user generated content in terms of resources to display the user generated content and based on the user generated content data structure and page information.

18. The computer-readable medium of claim 17, wherein the user generated content comprises at least one of notes, highlights and underlines made by users on pages of the markup language document.

19. The computer-readable medium of claim 13, further comprising instructions for:

receiving advertisement content associated with pages of the markup language document, the advertisement content to be displayed within pages of the markup language document and including content structure and page information associated with the advertisement content; and

creating advertisement content markers for the pages of the markup language document based on the received advertisement content, the advertisement content markers characterizing the complexity of the advertisement content in terms of memory resources to display the advertisements and based on the advertisement content structure and page information.

20. The computer-readable medium of claim 19, wherein the advertisement content comprises targeted advertisements received from an ad manifest, the ad manifest providing advertisements to be served within pages of the markup language document.

21. The computer-readable medium of claim 13, further comprising instructions for creating system reserved markers based on services that can be provided on a page of the document, the system reserved markers characterizing the complexity of service content that can be displayed with the markup language document, the service content providing at least one of interactive or social networking capabilities.

22. The computer-readable medium of claim 13, further comprising instructions for:

adding delta markers associated with each page of the markup language document, the delta markers comprising an estimated difference between page markers, related content markers, user generated content markers, advertisement content markers and system reserved markers;

calculating a difference between the added delta markers of consecutive pages of the markup language document; and

providing the calculated difference to the web browser application.

23. The computer-readable medium of claim 13, further comprising instructions for:

receiving performance feedback data characterizing the amount of processing power available to the web browser application responsive to receiving the marker data; and

changing content layers sent to the web browser application responsive to receiving the performance feedback data.

24. The computer-readable medium of claim 13, wherein the markup language document comprises an HTML5 document.