Updateable metadata for media content

• US 8,543,582 B1
• Filed: 08/26/2011
• Issued: 09/24/2013
• Est. Priority Date: 08/26/2011
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Granstrm, Johan Georg
• Primary Examiner(s): Wilson, Kimberly
• Assistant Examiner(s): Rayyan, Susan F
• Application Number:
  US13/218,615
• Time in Patent Office: 760 Days
• Field of Search: None
• US Class Current: 707/748
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually

Abstract

The subject disclosure relates to leveraging input from media consumers of media content with no or unstructured metadata in order to provide accurate and relevant structured metadata for the media content. Thus, media content uploaded to a content server can be associated with a set of predetermined metadata tags that are intended to be relevant to the media content and to accurately describe the media content. These tags can be implemented as key-value pairs, in which either the keys or the values for a given key can be provided by users (e.g., consumers of the media content), and any such input can be assigned a confidence score in order to determine the “correct” value for a key.

Claims

1. A system that associates metadata tags with media content, comprising:

a non-transitory memory that stores computer executable components; and

a processor that executes the following computer executable components stored in the non-transitory memory;

an archive component that receives media content from a content source and stores the media content to a content server configured to provide a content consumer access to the media content;

a tagging component that selects a set of tags that represent structured metadata that describe the media content, wherein a tag from the set of tags is implemented as a key-value pair with a key portion and a value portion, wherein the value portion of the tag relates to an updateable suggested value for the key portion, the tagging component further associates the set of tags with the media content; and

a population component configured to update the updateable suggested value based upon input received from the content consumer and a confidence metric associated with the input.

2. The system of claim 1, wherein the key portion of the tag relates to a feature associated with the media content that is determined relevant to users.

3. The system of claim 1, wherein, the tagging component selects the set of tags based upon a classification of the media content.

4. The system of claim 1, wherein the population component updates the set of tags further based upon input received from the content source.

5. The system of claim 1, wherein the population component adds a new tag to the set of tags based upon input received from the content consumer.

6. The system of claim 1, further comprising a ranking component that determines the confidence metric associated with an accuracy of a suggested value based upon an analysis of aggregate input from multiple content consumers.

7. The system of claim 6, wherein the ranking component determines the confidence metric based upon an equal weighting of respective input from the multiple content consumers.

8. The system of claim 6, wherein the ranking component determines the confidence metric based upon an unequal weighting of respective input from the multiple content consumers.

9. The system of claim 7, wherein the ranking component increases a vote weight associated with the content consumer based upon a history of validated input.

10. The system of claim 7, wherein the ranking component decreases a vote weight associated with the content consumer based upon a history of disputed input.

11. The system of claim 7, wherein the ranking component increases a vote weight associated with the content consumer based upon relevant expertise.

12. A system that updates metadata tags associated with media content, comprising:

a non-transitory memory that stores computer executable components; and

a processor that executes the following computer executable components stored in the non-transitory memory;

an interface component that presents a tag from a set of tags associated with media content, the tag is structured as a key-value pair with a key portion and a value portion;

a receiving component that receives a suggested value for the value portion of the tag from a consumer of the media content; and

a vetting component that determines a confidence score associated with an accuracy of the suggested value and that facilitates presentation of the confidence score and a first suggested value associated with a highest confidence score.

13. The system of claim 12, wherein the tag represents structured metadata in which the key portion relates to a feature associated with the media content that is determined relevant to the consumer and the value portion is the suggested value for the key portion with the highest confidence score.

14. The system of claim 12, wherein the interface component further presents the media content and a listing of comments associated with the media content.

15. The system of claim 14, further comprising a parsing component that extracts the suggested value from the listing of comments.

16. The system of claim 12, wherein the receiving component receives the suggested value in response to a selection of metadata included in a user interface.

17. The system of claim 12, wherein the interface component presents at least one additional suggested value associated with at least one lower confidence score that is lower than the highest confidence score.

18. The system of claim 17, wherein the interface component presents the at least one additional suggested value in connection with an expandable or collapsible user interface element.

19. The system of claim 12, wherein the receiving component further receives a suggested tag that is recommended to be included in the set of tags.

20. A method for presenting and updating metadata associated with media content, comprising:

employing a processor to execute computer executable components stored within a non-transitory memory to perform the following;

providing access by way of a computer network to media content;

presenting to a consumer of the media content updateable metadata describing at least one feature of the media content, wherein the updateable metadata is structured as a key-value pair;

receiving input from the consumer relating to the updateable metadata; and

updating the updatable metadata by transforming the updateable metadata in response to the input and a confidence rating associated with an accuracy of the input.

21. The method of claim 20, further comprising receiving the media content by way of a user upload.

22. The method of claim 20, further comprising associating the media content with the updateable metadata based upon a type of the media content.

23. The method of claim 20, wherein updating the updatable metadata comprises defining a new key-value pair of metadata for the media content.

24. The method of claim 20, wherein updating the updatable metadata comprises updating a suggested value associated with a value portion of the key-value pair for an existing key-value pair of the updateable metadata.

25. The method of claim 20, further comprising determining the confidence rating by analyzing aggregate input from multiple content consumers, wherein the aggregate input includes a vote for the suggested value or a vote against the suggested value.

26. The method of claim 20, further comprising employing a democratic model that equally weights inputs for determining the confidence rating.

27. The method of claim 20, further comprising employing a specialist model that applies greater weights to inputs from particular consumers than to other consumers when determining the confidence rating.

28. The method of claim 20, further comprising receiving the input from the consumer by way of at least one of an interface that present the updateable metadata or by extracting the input from a set of comments associated with the media content.