SYSTEM AND METHODS FOR THE AUTOMATIC TRANSMISSION OF NEW, HIGH AFFINITY MEDIA

• US 20090006321A1
• Filed: 09/10/2008
• Published: 01/01/2009
• Est. Priority Date: 07/06/2000
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Kaiser, Rolf, Bassman, Eric, Carreno, Michael J.
• Application Number:
  US12/208,241
• Publication Number:
  US 20090006321A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/4387 by the use of playlists
• 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 16/634 Query by example, e.g. query by humming
• CPC Class Codes: G06F 16/637 Administration of user profiles, e.g. generation, initialization, adaptation or distribution
• 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: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• 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 707/99937 Sorting
• CPC Class Codes: Y10S 707/99945 Object-oriented database structure processing
• CPC Class Codes: Y10S 707/99948 Application of database or data structure, e.g. distributed, multimedia, or image

Abstract

A system and methods for the automatic transmission of new, high affinity media to a user are provided. In connection with a system that convergently merges perceptual and digital signal processing analysis of media entities for purposes of classifying the media entities, various means are provided to a user for automatically extracting media entities that represent a high (or low) affinity state/space for the user in connection with the generation of a high affinity playlist, channel or station. Techniques for providing a dynamic recommendation engine and techniques for rating media entities are also included are also included. Once a high affinity state/space is identified, the high affinity state/space may be persisted for the user from experience to experience.

Claims

1. A method for generating a media playlist, comprising:

analyzing a selected media entity to determine a set of classification mappings;

receiving a rating for the selected media entity;

accessing a user'"'"'s media mappings, the media mappings determined as a function of the user'"'"'s past media ratings;

updating the user'"'"'s media mappings as a function of the received rating and said set of classification mappings;

generating the media playlist by searching a database of media entities and weighting each media entity such that the media entity is more likely to be included in the playlist when the media entity'"'"'s classification mapping corresponds to the user'"'"'s updated media mappings according to at least one criterion.

2. The method of claim 1, further comprising determining initial conditions for the user'"'"'s media mappings, comprising aggregating mappings of the user'"'"'s rated entities.

3. The method of claim 1, further comprising determining a high affinity space and a low affinity space as a function of the user'"'"'s media mappings.

4. The method of claim 3, wherein said weighting further comprises weighting each media entity as more likely to be included in the playlist when the media entity'"'"'s mapping is substantially similar to the user'"'"'s high affinity space and less likely to be included in the playlist when the media entity'"'"'s mapping is substantially similar to the user'"'"'s low affinity space.

5. The method of claim 4, wherein the media entity is blocked from entering the playlist when the media entity'"'"'s mapping is substantially similar to the user'"'"'s low affinity space and the number of media entities in the playlist meets a threshold level.

6. The method of claim 1, wherein the rating further comprises an active rating and at least one passive rating.

7. A computing system adapted to generate a media playlist, comprising:

a server; and

computing memory communicatively coupled to said server, the computing memory having stored therein a software application adapted to perform the following;

analyze a selected media entity to determine a set of classification mappings;

receive a rating for the selected media entity;

access a user'"'"'s media mappings, the media mappings determined as a function of the user'"'"'s past media ratings;

update the user'"'"'s media mappings as a function of the received rating and said set of classification mappings;

generate the media playlist by searching a database of media entities and weighting each media entity such that the media entity is more likely to be included in the playlist when the media entity'"'"'s classification mapping corresponds to the user'"'"'s updated media mappings according to at least one criterion.

8. A computer-readable storage medium comprising computer-executable instructions for generating a media playlist, the instructions for implementing steps comprising:

analyzing a selected media entity to determine a set of classification mappings;

receiving a rating for the selected media entity;

accessing a user'"'"'s media mappings, the media mappings determined as a function of the user'"'"'s past media ratings;

updating the user'"'"'s media mappings as a function of the received rating and said set of classification mappings;

generating the media playlist by searching a database of media entities and weighting each media entity such that the media entity is more likely to be included in the playlist when the media entity'"'"'s classification mapping corresponds to the user'"'"'s updated media mappings according to at least one criterion.