Automatic determination of whether a document includes an image gallery

• US 8,312,012 B1
• Filed: 07/23/2010
• Issued: 11/13/2012
• Est. Priority Date: 06/21/2004
• Status: Expired due to Fees

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Malpani, Radhika, Yang, Cheng, Zunger, Yonatan
• Primary Examiner(s): Leroux, Etienne
• Assistant Examiner(s): BIBBEE, JARED M
• Application Number:
  US12/842,545
• Time in Patent Office: 844 Days
• Field of Search: 707/706, 707/724
• US Class Current: 707/724
• CPC Class Codes: G06F 16/532 Query formulation, e.g. graphical querying
• CPC Class Codes: G06F 16/58 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06F 18/24 Classification techniques

Abstract

Image galleries are automatically located within documents, such as web pages. Documents that are determined to contain image galleries may be treated differently when storing the document for later retrieval by an image search engine. In one implementation, the image galleries are automatically located within a document by calculating position information indicating relative positions of images in the document. The document may be determined to contain an image gallery when the position information indicates that the images in the document are generally evenly distributed.

Claims

1. A method comprising:

generating, by a device, information that identifies horizontal distances and vertical distances between images in a document,

the horizontal distances and the vertical distances corresponding to distances between the images when the document is provided for display;

constructing, by the device, a graphical representation that is based on the information that identifies the horizontal distances and the vertical distances between the images in the document;

estimating, by the device, a likelihood that the document includes an image gallery based on a peak value of the graphical representation; and

storing, by the device and when the estimated likelihood indicates that the document includes the image gallery, in a memory;

information associated with the images, and

information indicating that the images are part of the image gallery.

2. The method of claim 1, further comprising:

parsing the document to determine that the document includes the images; and

generating the information that identifies the horizontal distances and the vertical distances, based on parsing the document, to determine that the document includes the images.

3. The method of claim 2, where generating the information that identifies the horizontal distances and the vertical distances includes:

generating, based on parsing the document to determine that the document includes the images, a table that includes a plurality of entries,

each of the plurality of entries identifying a different one of the images and text included in the document.

4. The method of claim 3, where the document includes a hyper text markup language (HTML) document, and

the method further comprising:

identifying, based on parsing the document, HTML tags that identify the images and the text; and

generating the table based on the HTML tags, where the plurality of entries are based on the HTML tags.

5. The method of claim 3, where each of the plurality of entries corresponds to coordinates of a different cell of a plurality of cells of the table, and

where generating the information that identifies the horizontal distances and the vertical distances includes generating the information that identifies the horizontal distances and the vertical distances based on the coordinates of cells, of the plurality of cells, associated with the images.

6. The method of claim 1, further comprising:

determining whether the images include links to other images or other documents,

where estimating the likelihood that the document includes the image gallery includes estimating the likelihood that the document includes the image gallery further based on determining whether the images include the links to the other images or the other documents.

7. The method of claim 1, further comprising:

determining whether sizes of the images are within a particular threshold,

where estimating the likelihood that the document includes the image gallery includes estimating the likelihood that the document includes the image gallery further based on determining whether the sizes of the images are within the particular threshold.

8. A device comprising:

a memory to store instructions; and

a processor to execute the instructions in the memory to;

generate information that identifies horizontal distances and vertical distances between images in a document,

the horizontal distances and the vertical distances corresponding to distances between the images when the document is provided for display,

construct a graphical representation that is based on the information that identifies the horizontal distances and the vertical distances between the images in the document,

estimate a likelihood that the document includes an image gallery based on a peak value of the graphical representation, and

store, when the estimated likelihood indicates that the document includes the image gallery, in a memory;

information associated with the images, and

information indicating that the images are part of the image gallery.

9. The device of claim 8, where the document includes a hyper text markup language (HTML) document, and

where the processor, when generating the information that identifies the horizontal distances and the vertical distances, is further to:

examine an HTML code of the document, and

identify HTML tags that identify the images based on examining the HTML code.

10. The device of claim 9, where, when generating the information that identifies the horizontal distances and the vertical distances, the processor is further to:

generate, based on the HTML tags, a table that includes a plurality of entries,

each of the plurality of entries identifying a different one of the images.

11. The device of claim 10, where each of the plurality of entries corresponds to coordinates of a different cell of a plurality of cells of the table, and

where, when generating the information that identifies the horizontal distances and the vertical distances, the processor is to:

generate, based on the coordinates of the plurality of cells, the information that identifies the horizontal distances and the vertical distances.

12. The device of claim 8, where the processor is further to:

determine whether the document includes one or more particular keywords,

where, when estimating the likelihood that the document includes the image gallery, the processor is to estimate the likelihood that the document includes the image gallery further based on determining whether the document includes the one or more particular keywords.

13. The device of claim 8, where the processor is further to:

determine whether the images correspond to a portion of the document that is less than a threshold portion of the document,

where, when estimating the likelihood that the document includes the image gallery, the processor is to estimate the likelihood that the document includes the image gallery further based on determining whether the images correspond to the portion of the document that is less than the threshold portion of the document.

14. The device of claim 8, where the processor is further to at least one of:

determine whether the images include links to other images or other documents, or

determine whether sizes of the images are within particular thresholds, and

where, when estimating the likelihood that the document includes the image gallery, the processor is to;

estimate the likelihood that the document includes the image gallery further based on the processor determining at least one of;

whether the sizes of the images are within the particular thresholds, or

whether the images include the links to the other images or the other documents.

15. A non-transitory computer-readable medium comprising:

a plurality of instructions which, when executed by a processor, cause the processor to;

generate information that identifies horizontal distances and vertical distances between images included in a document,

the horizontal distances and the vertical distances corresponding to distances between the images when the document is provided for display;

estimate a likelihood that the document includes an image gallery,

the likelihood being estimated based on the information that identifies the horizontal distances and the vertical distances between the images in the document; and

store, when the estimated likelihood indicates that the document includes the image gallery, in a memory;

information associated with the images, and

information indicating that the images are part of the image gallery.

16. The non-transitory computer-readable medium of claim 15, further comprising:

one or more instructions to construct a graphical representation that is based on the information that identifies the horizontal distances and the vertical distances between the images in the document; and

one or more instructions to estimate the likelihood that the document includes an image gallery based on a peak value of the graphical representation.

17. The non-transitory computer-readable medium of claim 15, where one or more instructions, of the plurality of instructions, to generate the information that identifies the horizontal distances and the vertical distances include:

one or more instructions to generate a table that includes a plurality of entries,

each of the plurality of entries identifying a different one of the images.

18. The non-transitory computer-readable medium of claim 17, further comprising one or more instructions to:

identify tags, in the document, that identify the images; and

generate the table based on the tags, where the plurality of entries are based on the tags.

19. The non-transitory computer-readable medium of claim 17, where each of the plurality of entries corresponds to coordinates of a different cell of a plurality of cells of the table, and

where one or more instructions, of the plurality of instructions, to generate the information that identifies the horizontal distances and the vertical distances include:

one or more instructions to generate the information that identifies the horizontal distances and the vertical distances based on the coordinates of the plurality of cells.

20. The non-transitory computer-readable medium of claim 15, further comprising one or more instructions to determine whether the document includes at least one of one or more particular keywords or links to other images or other documents,

where one or more instructions, of the plurality of instructions, to estimate the likelihood that the document includes the image gallery include:

one or more instructions to estimate the likelihood that the document includes the image gallery further based on determining whether the document includes the at least one of the one or more particular keywords or the links to the other images or the other documents.