Automatically associating archived multimedia content with current textual content

• US 5,905,981 A
• Filed: 12/09/1996
• Issued: 05/18/1999
• Est. Priority Date: 12/09/1996
• Status: Expired due to Term

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Lawler, Frank A.
• Primary Examiner(s): Amsbury, Wayne
• Assistant Examiner(s): Jung, David Yiuk
• Application Number:
  US08/762,430
• Time in Patent Office: 890 Days
• Field of Search: 707/1-206, 707/500-532
• US Class Current: 715/201
• CPC Class Codes: G06F 16/30 of unstructured textual data document management systems G06F16/93
• CPC Class Codes: G06F 40/106 Display of layout of documents; Previewing
• CPC Class Codes: G06F 40/174 Form filling; Merging
• CPC Class Codes: Y10S 707/915 Image
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access

Abstract

Described herein is a system that draws from an archive of media objects to associate appropriate media objects with current news articles. The media object archive includes an index having an entry for each media object. The index associates a set of one or more keywords with each media object, and a set of one or more search criteria with each media object. With regard to a particular news story, the system first identifies an initial group of relevant media objects having associated keywords that are contained in the news story. The system then evaluates the search criteria associated with each media object in the identified group against the news story, and limits the group by removing any media object from the group if the search criteria associated with that media object are not satisfied by the news story. A remaining media object from this limited group is then selected for association with the news story.

Claims

1. A method of selecting one of a plurality of media objects to associate with specified textual content, comprising the following steps:

associating a set of one or more keywords with each media object;

associating a set of one or more search criteria with each media object;

identifying a group of relevant media objects having associated keywords that are contained in the specified textual content;

evaluating the search criteria associated with each media object in the identified group against the specified textual content;

limiting the group by removing any media object from the group if the search criteria associated with that media object are not satisfied by the specified textual content;

selecting a remaining media object from the limited group to associate with the specified textual content.

2. A method as recited in claim 1, the step of identifying a group of relevant media objects comprising identifying those media objects whose keywords occur most often in the specified textual content.

3. A method as recited in claim 1, the selecting step comprising selecting a media object from the limited group whose keywords occur most often in the specified textual content.

4. A method as recited in claim 1, further comprising maintaining a historical usage database to track usage of the media objects.

5. A method as recited in claim 1, wherein the selected media object is an image, further comprising showing the selected image along with the specified textual content.

6. A computer programmed to perform the steps recited in claim 1.

7. A computer-readable storage medium having instructions for performing the steps recited in claim 1.

8. An automated method for associating images with news feed articles, comprising the following steps:

obtaining a plurality of images;

associating a set of one or more keywords with each image;

associating a set of one or more search criteria with each image in addition to the set of one or more keywords;

selecting a particular article from a news feed;

identifying a group of relevant images having associated keywords that are contained in a portion of the particular article from the news feed;

evaluating the search criteria associated with each image in the identified group against the portion of the particular article;

limiting the group by removing any image from the group if the search criteria associated with that image is not satisfied by the portion of the particular article;

associating a remaining image from the limited group with the portion of the particular article.

9. A method as recited in claim 8, the step of identifying a group of relevant images comprising identifying those images whose keywords occur most often in the portion of the particular article.

10. A method as recited in claim 8, the step of associating a remaining image from the limited group with the portion of the particular article comprising selecting an image from the limited group whose keywords occur most often in the portion of the particular article.

11. A method as recited in claim 8, further comprising maintaining a historical usage database to track usage of the images.

12. A computer programmed to perform the steps recited in claim 8.

13. A computer-readable storage medium having instructions for performing the steps recited in claim 8.

14. A computer-readable medium having computer-executable instructions for performing steps to select one of a plurality of media objects to associate with a specified textual content, the steps comprising:

associating a set of one or more keywords with each media object;

associating a set of one or more search criteria with each media object;

identifying a group of relevant media objects having associated keywords that are contained in the specified textual content;

evaluating the search criteria associated with each media object in the identified group against the specified textual content;

limiting the group by removing any media object from the group if the search criteria associated with that media object are not satisfied by the specified textual content;

selecting a remaining media object from the limited group to associate with the specified textual content.

15. A computer-readable medium as recited in claim 14, the step of identifying a group of relevant media objects comprising identifying those media objects whose keywords occur most often in the specified textual content.

16. A computer-readable medium as recited in claim 14, the selecting step comprising selecting a media object from the limited group whose keywords occur most often in the specified textual content.

17. A computer-readable medium as recited in claim 14, the steps further comprising maintaining a historical usage database to track usage of the media objects.

18. A computer-readable medium as recited in claim 14, wherein the selected media object is an image, the steps further comprising showing the selected image along with the specified textual content.