System and method for generating metadata for programming events

• US 20020092031A1
• Filed: 11/16/2001
• Published: 07/11/2002
• Est. Priority Date: 11/16/2000
• Status: Active Grant

• Current Assignee: MeeVee, Inc. (LiveUniverse, Inc.)
• Original Assignee: MeeVee, Inc. (LiveUniverse, Inc.)
• Inventors: Hitt, Dale Kittrick, Dudkiewicz, Gil Gavriel
• Granted Patent: US 7,367,043 B2
• Time in Patent Office: Days
• US Class Current: 725/138
• 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 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/735 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/78 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: H04N 21/235 Processing of additional data, e.g. scrambling of additional data or processing content descriptors
• CPC Class Codes: H04N 21/4305 Synchronising client clock from received content stream, e.g. locking decoder clock with encoder clock, extraction of the PCR packets arrangements for synchronising receiver with transmitter by comparing receiver clock with transmitter clock H04L7/0012; arrangements for synchronising receiver with transmitter wherein the receiver takes measures against momentary loss of synchronisation H04L7/0083
• CPC Class Codes: H04N 21/4334 Recording operations recording of a television signal H04N5/76; arrangements for recording or accumulating broadcast information or broadcast-related information H04H60/27
• CPC Class Codes: H04N 21/435 Processing of additional data, e.g. decrypting of additional data, reconstructing software from modules extracted from the transport stream
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/454 Content or additional data filtering, e.g. blocking advertisements
• CPC Class Codes: H04N 21/466 Learning process for intelligent management, e.g. learning user preferences for recommending movies services using the results of monitoring in broadcast systems H04H60/61
• CPC Class Codes: H04N 21/4661 Deriving a combined profile for a plurality of end-users of the same client, e.g. for family members within a home user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 21/4665 involving classification methods, e.g. Decision trees
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/4755 for defining user preferences, e.g. favourite actors or genre retrieval personalisation and generation of user profiles for the retrieval of video data G06F16/739; user profiles in network data switching protocols H04L67/306
• CPC Class Codes: H04N 21/4854 for modifying image parameters, e.g. image brightness, contrast
• CPC Class Codes: H04N 21/8405 represented by keywords
• CPC Class Codes: H04N 21/8543 using a description language, e.g. Multimedia and Hypermedia information coding Expert Group [MHEG], eXtensible Markup Language [XML] information retrieval of semistructured data, the underlying structure being taken into account, e.g. mark-up language structure data G06F16/80
• CPC Class Codes: H04N 5/781 on disks or drums
• CPC Class Codes: H04N 5/782 on tape
• CPC Class Codes: H04N 5/85 : on discs or drums
• CPC Class Codes: H04N 7/163 : by receiver means only
• CPC Class Codes: Y10S 707/99932 : Access augmentation or optimizing
• 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 707/99943 : Generating database or data structure, e.g. via user interface

Abstract

Metadata for a programming event may be generated by receiving descriptive information and timing information for the programming event and analyzing this information to determine category goodness of fit scores for the programming event corresponding to categories of a classification hierarchy. The information is further analyzed to determine keywords associated with the programming event. The category goodness of fit scores and keywords may be stored along with time data and descriptive data for the programming event as metadata for the programming event. Goodness of fit scores may also be generated for the keywords. Related embodiments may pertain to a device implementing such processing. Keyword metadata may be generated using candidate keywords taken from descriptive data associated with the programming event. The candidate key words may be provided individually as inputs to a classification tool configured to generate goodness of fit scores for categories of a classification hierarchy. Keywords may then be selected from among the candidates based on their individual scores, and stored as part of the metadata for the programming event. The scores of the keywords may be stored in association with the keywords.

Claims

1. A method for generating metadata for a programming event comprising:

receiving data corresponding to a programming event, the data including descriptive information and timing information;

analyzing the received data to determine category goodness of fit scores for the programming event corresponding to categories of a classification hierarchy;

analyzing the received data to determine keywords associated with the programming event; and

storing category goodness of fit scores and keywords in association with time data and descriptive data for the programming event as metadata for the programming event.

2. The method claimed in claim 1, further comprising determining respective keyword goodness of fit scores for said determined keywords.

3. The method claimed in claim 2, further comprising determining a representative subset of said determined keywords by a thresholding procedure using said keyword goodness of fit scores, and

wherein storing keywords comprises storing said representative subset of keywords and corresponding keyword goodness of fit scores as part of said metadata.

4. The method claimed in claim 1, further comprising determining a representative subset of said category goodness of fit scores, and

wherein storing category goodness of fit scores comprises storing said representative subset of said category goodness of fit scores.

5. The method claimed in claim 1, wherein the received data comprises program descriptive data data.

6. The method claimed in claim 1, wherein the received data comprises production data including descriptive information and timing information.

7. The method claimed in claim 6, wherein analyzing the received data is preceded by determining a time and a duration of individual segments of a program described by the production data.

8. The method claimed in claim 7, wherein determining a time and duration is preceded by processing the production data to conform to a standard delimited format.

9. The method claimed in claim 7, wherein the received data further comprises program descriptive data data describing the program.

10. The method claimed in claim 1, wherein storing keywords comprises storing no more than a predetermined number of keywords.

11. A device for generating metadata for a programming event comprising:

at least one processor; and

memory coupled to the at least one processor and having stored therein programming instructions to perform data processing, comprising;

receiving data corresponding to a programming event, the data including descriptive information and timing information;

analyzing the received data to determine category goodness of fit scores for the programming event corresponding to categories of a classification hierarchy;

analyzing the received data to determine keywords associated with the programming event; and

storing category goodness of fit scores and keywords in association with time data and descriptive data for the programming event as metadata for the programming event.

12. The device claimed in claim 11, said processing further comprising determining respective keyword goodness of fit scores for said determined keywords.

13. The device claimed in claim 12, said processing further comprising determining a representative subset of said determined keywords by a thresholding procedure using said keyword goodness of fit scores, and

wherein storing keywords comprises storing said representative subset of keywords and corresponding keyword goodness of fit scores as part of said metadata.

14. The device claimed in claim 11, said processing further comprising determining a representative subset of said category goodness of fit scores, and

wherein storing category goodness of fit scores comprises storing said representative subset of said category goodness of fit scores.

15. The device claimed in claim 11, wherein the received data comprises program descriptive data data.

16. The device claimed in claim 11, wherein the received data comprises production data including descriptive information and timing information.

17. The device claimed in claim 16, wherein analyzing the received data is preceded by determining a time and a duration of individual segments of a program described by the production data.

18. The device claimed in claim 17, wherein determining a time and duration is preceded by processing the production data to conform to a standard delimited format.

19. The device claimed in claim 17, wherein the received data further comprises program descriptive data data describing the program.

20. The device claimed in claim 11, wherein storing keywords comprises storing no more than a predetermined number of keywords.

21. A method for generating metadata for a programming event comprising:

determining candidate keywords from descriptive data associated with the programming event;

providing the candidate keywords as input to a classification tool configured to generate goodness of fit scores for categories of a classification hierarchy;

selecting keywords from among said candidate keywords based on category goodness of fit scores generated for each of said candidate keywords by the classification tool; and

storing said selected keywords as a component of metadata for the programming event.

22. The method claimed in claim 21, wherein determining candidate keywords comprise determining verbs and nouns of said descriptive data.

23. The method claimed in claim 21, wherein selecting keywords is preceded by:

correlating category goodness of fit scores of said candidate keywords to category goodness of fit scores of said programming event; and

discarding candidate keywords having low correlation.

24. The method claimed in claim 21, wherein selecting keywords comprises eliminating candidate keywords by a thresholding process using a highest category goodness of fit score associated with each candidate keyword.

25. The method claimed in claim 21, further comprising storing a highest category goodness of fit score associated with each selected keyword as a corresponding keyword goodness of fit score.

26. The method claimed in claim 21, wherein storing selected keywords comprises storing no more than a predetermined number of selected keywords.

28. The device claimed in claim 27, wherein determining candidate keywords comprise determining verbs and nouns of said descriptive data.

29. The device claimed in claim 27, wherein selecting keywords is preceded by:

correlating category goodness of fit scores of said candidate keywords to category goodness of fit scores of said programming event; and

discarding candidate keywords having low correlation.

30. The device in claim 27, wherein selecting keywords comprises eliminating candidate keywords by a thresholding process using a highest category goodness of fit score associated with each candidate keyword.

31. The device claimed in claim 27, said processing further comprising storing a highest category goodness of fit score associated with each selected keyword as a corresponding keyword goodness of fit score.

32. The device claimed in claim 27, wherein storing selected keywords comprises storing no more than a predetermined number of selected keywords.

27. A device for generating metadata for a programming event comprising:

at least one processor; and

memory coupled to the at least one processor and having stored therein programming instructions to perform data processing, comprising;

determining candidate keywords from descriptive data associated with the programming event;

providing the candidate keywords as input to a classification tool configured to generate goodness of fit scores for categories of a classification hierarchy;

selecting keywords from among said candidate keywords based on category goodness of fit scores generated for each of said candidate keywords by the classification tool; and

storing said selected keywords as a component of metadata for the programming event.