Interest Learning from an Image Collection for Advertising

• US 20110072047A1
• Filed: 09/21/2009
• Published: 03/24/2011
• Est. Priority Date: 09/21/2009
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Wang, Xin-Jing, Ma, Wei-Ying, Zhang, Lei
• Application Number:
  US12/563,955
• Publication Number:
  US 20110072047A1
• Time in Patent Office: Days
• US Class Current: 707/776
• 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 16/583 using metadata automatically derived from the content

Abstract

Described herein is a technology that facilitates learning interests for advertising based on automated analysis of images. In several embodiments a person'"'"'s interests are automatically learned based on the person'"'"'s photographs for targeted advertising. Techniques are described that facilitate automatically detecting a user'"'"'s interest from images and suggesting user-targeted ads. As described herein, these techniques include computer-annotating images with learned tags, performing topic learning to obtain an interest model, and performing advertisement matching and ranking based on the interest model.

Claims

1. A computer-readable medium having computer executable instructions encoded thereon, the computer executable instructions encoded for execution by a processor to configure the computer to perform interest mining operations comprising:

identifying a collection of one or more images associated with a user;

mining image content information of an image from the collection;

based at least on the image content information, determining an annotation corresponding to the image associated with the user, wherein determining the annotation corresponding to the image associated with the user is based at least in part on at least one of;

locating in an image repository using the image content information, an image that is graphically similar to the image associated with the user and mining descriptive data corresponding to the image that is graphically similar to the image associated with the user to derive a learned tag;

processing descriptive data corresponding to the image found in the image repository that is graphically similar to the image associated with the user to derive the learned tag;

annotating the image associated with the user with the learned tag;

based at least on the learned tag, deriving a topic of the image associated with the user;

obtaining a description of a product;

based at least on the description of the product, determining a topic of the product;

mapping the topic of the image associated with the user with the topic of the product;

repeating the mapping for a configurable number of products;

based at least on the mapping, calculating a ranking of topics of products in relation to the topic of the image associated with the user;

obtaining advertising for a configurable number of products based at least on the ranking;

providing a configurable number of advertisements from the obtained advertising.

2. A computer-readable medium as recited in claim 1, wherein the operations further comprise soliciting product advertising based at least on the derived topic of the collection of one or more images associated with the user.

3. A computer-readable medium as recited in claim 1, wherein the images associated with the user comprise informal images comprising one or more of:

photographs taken with a cellular telephone;

photographs taken with a digital camera;

photographs scanned by users;

photographs emailed by users;

photographs saved by users.

4. A method of selecting advertising comprising:

identifying a collection of one or more images;

determining a collection topic for the collection of one or more images;

determining a product topic corresponding to each of a plurality of product advertisements;

searching among the product topics to find one or more product topics similar to the collection topic;

selecting those product advertisements corresponding to the similar product topics.

5. A method as recited in claim 4, wherein determining a collection topic comprises:

for each image of the collection, searching for graphically similar images, the graphically similar images having associated descriptive data;

searching a topic space based on the associated descriptive data of the graphically similar images.

6. A method as recited in claim 4, wherein at least one of the collection of one or more images has associated descriptive data, and wherein determining a collection topic comprises:

for each image of the collection, searching for graphically similar images, the graphically similar images having associated descriptive data;

searching a topic space based on the associated descriptive data of the graphically similar images and on the descriptive data of the collection of one or more images.

7. A method as recited in claim 4, further comprising:

creating a hierarchical topic ontology;

wherein determining a collection topic comprises;

for each image of the collection, searching for graphically similar images, the graphically similar images having associated descriptive data;

searching the hierarchical topic space based on the associated descriptive data of the graphically similar images.

8. A method as recited in claim 4, wherein the collection of one or more images comprises a plurality of images to be displayed together on a web page.

9. A method as recited in claim 4, wherein the collection of one or more images comprises a plurality of images that have been grouped together by a user.

10. A method as recited in claim 4, wherein determining a product topic comprises:

searching a topic space based on textual data associated with the product advertisements.

11. A method of Internet advertising, comprising:

identifying a collection of one or more images associated with Internet browsing activities of a user;

searching an image library for images that are graphically similar to the collection of one or more images associated with the Internet browsing activities of the user, the graphically similar images having associated descriptive data;

processing the descriptive data of the graphically similar images to derive a topic for the collection of one or more images associated with the Internet browsing activities of the user;

selecting advertising based at least in part on the derived topic; and

presenting the selected advertising to the user in response to the browsing activities of the user.

12. A method as recited in claim 11, wherein processing the descriptive data comprises searching a product topic space based on the descriptive data.

13. A method as recited in claim 11, wherein identifying the collection of one or more images comprises identifying one or more images of a web page requested by the user.

14. A method as recited in claim 11, wherein identifying the collection of one or more images comprises identifying images that have been grouped together by the user.

15. A method as recited in claim 11, wherein searching the image library comprises:

deriving image content information from each of the one or more images associated with Internet browsing activities of a user;

comparing the derived image content information to image content information of images in the image library.

16. A method as recited in claim 11, wherein processing the descriptive data comprises:

removing stop words from the descriptive data of the graphically similar images;

mining the descriptive data of the graphically similar images for one or more terms;

applying the one or more terms to the one or more images associated with the Internet browsing activities of the user to derive the topic for the collection of one or more images associated with the Internet browsing activities of the user.

17. A method as recited in claim 11, wherein processing the descriptive data comprises:

removing stop words from the descriptive data of the graphically similar images;

mining the descriptive data of the graphically similar images for one or more terms;

applying the one or more terms to the one or more images associated with the Internet browsing activities of the user as learned tags;

deriving the topic for the collection of one or more images associated with the Internet browsing activities of the user from one or more of the learned tags.

18. A method as recited in claim 11, wherein selecting advertising comprises comparing the derived topic to advertising topics.

19. A method as recited in claim 11, further comprising serving the advertising based at least on a ranking of the advertising topics compared with the derived topic.

20. A method as recited in claim 11, wherein presenting the selected advertising comprises displaying the selected advertising on a web page along with the one or more images associated with the Internet browsing activities of the user.