Automated selection of images for web pages

• US 9,477,773 B2
• Filed: 08/24/2015
• Issued: 10/25/2016
• Est. Priority Date: 06/07/2000
• Status: Expired due to Term

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Pearson, Jennifer, Wang, Hsiaozhang Bill
• Primary Examiner(s): Nguyen, Maikhanh
• Application Number:
  US14/834,152
• Publication Number:
  US 20150363506A1
• Time in Patent Office: 428 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 16/986 Document structures and storage, e.g. HTML extensions
• CPC Class Codes: G06F 40/117 Tagging; Marking up details of markup languages G06F40/143; Designating a block; Setting of attributes style sheets, e.g. eXtensible Stylesheet Language Transformation [XSLT], G06F40/154
• CPC Class Codes: G06F 40/166 Editing, e.g. inserting or deleting
• CPC Class Codes: G06Q 30/08 Auctions

Abstract

In various embodiments, a method, a system, and a computer-readable medium are disclosed for creating a pool of images available for display, such as in one or more web pages. In one embodiment, a method is disclosed that includes selecting images for a markup language document by determining a pre-determined number, N, of images to display in the markup language document, encoding an instruction in the markup language document to be executed by one or more hardware-based processors to select N images for insertion into the markup language document, retrieving the N images from a group of images, and placing the N retrieved images in the markup language document. Other embodiments are also disclosed.

Claims

1. A method of selecting images for a markup language document, the method comprising:

determining a pre-determined number, N, of images to display in the markup language document;

encoding an instruction in the markup language document to be executed by one or more hardware-based processors to select N images for insertion into the markup language document;

retrieving the N images from a group of images; and

placing the N retrieved images in the markup language document,

wherein selecting the N images includes;

obtaining filtering criteria;

identifying an image from all available images based on the filtering criteria; and

adding the identified image to the group of images.

2. The method of claim 1, further comprising placing the N retrieved images in the markup language document at one or more respective locations defined in the instruction, the N images to be displayed on one or more web pages.

3. The method of claim 1, further comprising selecting the images from the group of images that have been previously stored in a data structure, the data structure including data associated with the item including an identifier of the image and a category for the image.

4. The method of claim 1, further comprising automatically regenerating a new set of N images to be placed in the markup language document at periodic intervals.

5. The method of claim 1, further comprising:

requesting N random numbers from a random-number generator; and

retrieving the N images using the N random numbers.

6. The method of claim 1, further comprising:

examining information associated with an identified image of the N images against a set of standards; and

based on a determination that the information does not meet at least a portion of the set of standards, discarding the identified image.

7. The method of claim 6, further comprising substituting a different image for the discarded image.

8. The method of claim 1, wherein the markup language document is a web page and the instruction is a tag in a proprietary format.

9. The method of claim 8, wherein the proprietary format comprises a widget identifier and one or more display parameters.

10. The method of claim 9, wherein the one or more display parameters comprise a size parameter and a location parameter.

11. The method of claim 1, further comprising:

validating the N images against validation criteria; and

based on a determination that an image fails the validation criteria, substituting a different image for the failed image.

12. A tangible machine-readable storage medium having no transitory signals and storing a set of instructions that, when executed by one or more hardware-based processors, causes the one or more processors to perform operations to select images for a markup language document, the operations comprising:

determining a pre-determined number, N, of images to display in the markup language document;

encoding an instruction in the markup language document to be executed by the one or more hardware-based processors to select N images for insertion into the markup language document;

retrieving the N images from a group of images; and

placing the N retrieved images in the markup language document,

wherein selecting the N images includes further operations comprising;

obtaining filtering criteria;

identifying an image from all available images based on the filtering criteria; and

adding the identified image to the group of images.

13. The tangible machine-readable storage medium of claim 12, wherein the operations further comprise placing the N retrieved images in the markup language document at one or more respective locations defined in the instruction, the N images to be displayed on one or more web pages.

14. The tangible machine-readable storage medium of claim 12, wherein the operations further comprise automatically regenerating a new set of N images to be placed in the markup language document at periodic intervals.

15. The tangible machine-readable storage medium of claim 12, wherein the operations further comprise:

requesting N random numbers from a random-number generator; and

retrieving the N images using the N random numbers.

16. The tangible machine-readable storage medium of claim 12, wherein the operations further comprise:

validating the N images against validation criteria; and

based on a determination that an image fails the validation criteria, substituting a different image for the failed image.