Auto playlist generator

• US 7,313,571 B1
• Filed: 10/31/2005
• Issued: 12/25/2007
• Est. Priority Date: 05/30/2001
• Status: Expired due to Fees

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Platt, John C., Weare, Christopher B., Burges, Christopher, Swenson, Steven E., Zheng, Alice
• Primary Examiner(s): Alam; Shahid Al
• Application Number:
  US11/263,347
• Time in Patent Office: 785 Days
• Field of Search: 707/6, 707/10, 707/2, 707/3, 707/102, 707/104.1, 707/200, 713/193, 846/01, 846/09, 352/40
• US Class Current: 1/1
• CPC Class Codes: G06F 16/634 Query by example, e.g. query by humming
• CPC Class Codes: G06F 16/639 using playlists
• CPC Class Codes: G06F 16/68 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/683 using metadata automatically derived from the content
• CPC Class Codes: Y10S 707/916 Audio
• 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 707/99935 Query augmenting and refining, e.g. inexact access
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing

Abstract

A system and method for generating a list is provided. The system includes a seed item input subsystem, an item identifying subsystem, a descriptive metadata similarity determining subsystem and a list generating subsystem that builds a list based, at least in part, on similarity processing performed on seed item descriptive metadata and user item descriptive metadata and user selected thresholds applied to such similarity processing. The method includes inexact matching between identifying metadata associated with new user items and identifying metadata stored in a reference metadata database. The method further includes subjecting candidate user items to similarity processing, where the degree to which the candidate user items are similar to the seed item is determined, and placing user items in a list of items based on user selected preferences for (dis)similarity between items in the list and the seed item.

Claims

1. A system having processor and memory associated therewith for generating one or more lists, the system comprising:

means for learning, the means for learning employing descriptive metadata from a training set of media objects to learn;

means for generating a fingerprint of a media object from a plurality of descriptive metadata attributes, at least one of the plurality of descriptive metadata attributes being a subjective attribute;

means for comparing the fingerprint to a reference fingerprint to produce an output indicative of the similarity between the fingerprints;

means for translating the output into a similarity value, wherein the means for translating is generated at least in part by the means for learning; and

means for generating a list of similar media objects based on the similarity value, wherein the similarity value is a difference vector, where the difference is taken between two different feature vectors, each of which describes an item in the media library data store and a training item.

2. The system of claim 1, wherein the list of candidate items is presented to a user and generated on the user'"'"'s computer.

3. The system of claim 1, further comprising a media library data store that stores user items.

4. The system of claim 3, the media library data store resides on a client device.

5. The system of claim 1, further comprising a reference metadata database that stores as-added descriptive metadata associated with the media object.

6. The system of claim 5, the descriptive metadata comprises information concerning the genre of the object.

7. The system of claim 1, the media objects comprises at least one of songs, music videos, movies, documents, books and images.

8. A method for generating one or more lists, the system comprising:

generating a fingerprint of a media object from a plurality of descriptive metadata attributes,

at least one of the plurality of descriptive metadata attributes being a subjective attribute;

comparing the fingerprint of the training media object to the fingerprint of a media object in the user data store to produce an output indicative of the similarity between the fingerprints;

translating the output into a similarity value; and

generating a list of similar media objects based on the similarity value,

wherein the similarity value is a difference vector, where the difference is taken between two different feature vectors, each of which describes an item in the media library data store and a training item.

9. The method of claim 8, further comprising a media library data store that stores user items.

10. The method of claim 8, further comprising a reference metadata database that stores as-added descriptive metadata associated with the media objects.

11. The method of claim 8, the different feature vectors are compared attribute by attribute to produce the difference vector.