Validating document content prior to format conversion based on a calculated threshold as a function of document size

• US 9,996,501 B1
• Filed: 06/28/2012
• Issued: 06/12/2018
• Est. Priority Date: 06/28/2012
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Nelson, Laura Ann, Bacus, Michael Patrick, Zhang, Xuping
• Primary Examiner(s): Paula, Cesar
• Assistant Examiner(s): Nguyen, Luu-Phuong
• Application Number:
  US13/535,661
• Time in Patent Office: 2,175 Days
• Field of Search: 715201
• CPC Class Codes: G06F 16/40 of multimedia data, e.g. slideshows comprising image and additional audio data retrieval of still image data G06F16/50; retrieval of audio data G06F16/60; retrieval of video data G06F16/70
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00
• CPC Class Codes: G06F 40/103 Formatting, i.e. changing of presentation of documents automatic justification G06F40/189; automatic line break hyphenation G06F40/191
• CPC Class Codes: G06F 40/143 Markup, e.g. Standard Generalized Markup Language [SGML] or Document Type Definition [DTD]
• CPC Class Codes: G06F 40/166 Editing, e.g. inserting or deleting
• CPC Class Codes: G06N 3/02 Neural networks
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/082 modifying the architecture, e.g. adding, deleting or silencing nodes or connections
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems
• CPC Class Codes: H03M 7/30 Compression speech analysis-synthesis for redundancy reduction G10L19/00; for image communication H04N; Expansion; Suppression of unnecessary data, e.g. redundancy reduction

Abstract

A content validation module receives an electronic media item in a first format. The content validation module may determine whether the electronic media item will contain errors when the electronic media item is converted to a second format. The content validation module may also obtain an error metric for the electronic media item and may refrain from converting the electronic media item to the second format if the error metric exceeds an error threshold.

Claims

1. A method comprising:

receiving, by a processing device, an electronic publication in a first format;

generating, by the processing device, a document object model (DOM) tree for the electronic publication;

prior to conversion of the electronic publication to a second format, determining, by the processing device, the electronic publication will contain errors after conversion of the electronic publication to the second format by applying one or more rules associated with the second format to the DOM tree and identifying a plurality of errors in the electronic publication;

determining, by the processing device, a first error type associated with a first error of the plurality of errors;

determining, by the processing device, a second error type associated with a second error of the plurality of errors;

assigning a first weight to the first error type and a second weight to the second error type, wherein the first weight represents a severity associated with the first error type, and wherein the second weight represents a severity associated with the second error type;

calculating, by the processing device, an error metric based on the first weight assigned to the first error type and the second weight assigned to the second error type;

determining, by the processing device, a size of the electronic publication;

calculating, by the processing device, an error threshold as a function of the size of the electronic publication, wherein the error threshold is directly proportional to the size of the electronic publication;

determining, by the processing device, the error metric does not exceed the error threshold; and

converting the electronic publication from the first format to the second format in response to determining the error metric does not exceed the error threshold.

2. The method of claim 1, further comprising:

highlighting one or more portions in the content of the electronic publication, wherein each of the one or more portions corresponds to a source of one of the one or more errors;

receiving user input indicative of one or more corrections for the one or more errors;

updating the electronic publication based on the user input.

3. The method of claim 1, wherein generating a document object model (DOM) tree for the electronic publication comprises:

converting the electronic publication to an intermediate format; and

generating the DOM tree based on the intermediate format.

4. The method of claim 3, wherein the intermediate format comprises at least one of a hypertext markup language format and an extensible markup language format.

5. The method of claim 1, wherein the one or more rules indicate a combination of a first node of the DOM tree and a second node of the DOM tree constitutes an error.

6. An apparatus comprising:

a processing device to;

receive an electronic publication in a first format;

prior to conversion of the electronic publication to a second format, determine the electronic publication will contain one or more errors upon conversion of the electronic publication to the second format by applying one or more rules associated with the second format to a document object model (DOM) tree for the electronic publication and identify a plurality of errors in the electronic publication;

determine a first error type associated with a first error of the plurality of errors;

determine a second error type associated with a second error of the plurality of errors;

assign a first weight to the first error type and a second weight to the second error type, wherein the first weight represents a severity associated with the first error type, and wherein the second weight represents a severity associated with the second error type;

calculate an error metric based on the first weight assigned to the first error type and the second weight assigned to the second error type;

determine, by the processing device, a size of the electronic publication;

calculate an error threshold as a function of the size of the electronic publication, wherein the error threshold is directly proportional to the size of the electronic publication;

determine the error metric does not exceed the error threshold; and

convert the electronic publication from the first format to the second format in response to a determination that the error metric does not exceed the error threshold.

7. The apparatus of claim 6, the processing device to:

convert the electronic publication to an intermediate format; and

generate the DOM tree based on the intermediate format.

8. The apparatus of claim 7, wherein the intermediate format comprises at least one of a hypertext markup language format and an extensible markup language format.

9. The apparatus of claim 6, wherein the one or more rules indicate a combination of a first node of the DOM tree and a second node of the DOM tree constitutes an error.

10. The apparatus of claim 6, wherein the processing device to:

highlight one or more portions in the content of the electronic publication, wherein each of the one or more portions corresponds to a source of one of the one or more errors;

receive user input indicative of one or more corrections for the one or more errors; and

update the electronic publication based on the user input.

11. The apparatus of claim 6, wherein the second format supports one or more of security features or digital rights management features.

12. The apparatus of claim 6, wherein the one or more errors comprise one or more of informational errors, content errors, formatting errors or display errors.

13. The apparatus of claim 12, wherein the processing device to:

determine a number of informational errors in the electronic publication.

14. A non-transitory computer-readable storage medium storing instructions which, when executed, cause a processing device to perform a method comprising:

receiving, by the processing device, an electronic publication in a first format;

prior to conversion of the electronic publication to a second format, determining, by the processing device, the electronic publication will contain one or more errors upon conversion of the electronic publication to the second format by applying one or more rules associated with the second format to a document object model (DOM) tree for the electronic publication and identifying a plurality of errors in the electronic publication;

determining, by the processing device, a first error type associated with a first error of the plurality of errors;

determining, by the processing device, a second error type associated with a second error of the plurality of errors;

assigning a first weight to the first error type and a second weight to the second error type, wherein the first weight represents a severity associated with the first error type, and wherein the second weight represents a severity associated with the second error type;

calculating, by the processing device, an error metric based on the first weight assigned to the first error type and the second weight assigned to the second error type;

determining, by the processing device, a size of the electronic publication;

calculating, by the processing device, an error threshold as a function of the size of the electronic publication, wherein the error threshold is directly proportional to the size of the electronic publication;

determining, by the processing device, the error metric does not exceed the error threshold; and

converting the electronic publication from the first format to the second format in response to determining the error metric does not exceed the error threshold.

15. The non-transitory computer-readable storage medium of claim 14, wherein the DOM tree for the electronic publication is generated by:

converting the electronic publication to an intermediate format; and

generating the DOM tree based on the intermediate format.

16. The non-transitory computer-readable storage medium of claim 15, wherein the intermediate format comprises at least one of a hypertext markup language format and an extensible markup language format.

17. The non-transitory computer-readable storage medium of claim 14, wherein the one or more rules indicate a combination of a first node of the DOM tree and a second node of the DOM tree constitutes an error.

18. The non-transitory computer-readable storage medium of claim 14, wherein the method further comprises:

highlighting one or more portions in the content of the electronic publication, wherein each of the one or more portions corresponds to a source of one of the one or more errors;

receiving user input indicative of one or more corrections for the one or more errors; and

updating the electronic publication based on the user input.

19. The non-transitory computer-readable storage medium of claim 14, wherein the second format supports one or more of security features or digital rights management features.

20. The non-transitory computer-readable storage medium of claim 14, wherein the one or more errors comprise one or more of informational errors, content errors, formatting errors or display errors.

21. The non-transitory computer-readable storage medium of claim 20, wherein the method further comprises:

determining a number of informational errors in the electronic publication.