Method and system for generating affinity based playlists

• US 20060195516A1
• Filed: 02/28/2006
• Published: 08/31/2006
• Est. Priority Date: 02/28/2005
• Status: Active Grant

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Beaupre, Todd
• Granted Patent: US 7,747,620 B2
• Time in Patent Office: Days
• US Class Current: 709/203
• CPC Class Codes: G06F 16/273 Asynchronous replication or reconciliation
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 16/4387 by the use of playlists
• CPC Class Codes: G06F 16/4393 Multimedia presentations, e.g. slide shows, multimedia albums
• 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 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 21/10 Protecting distributed programs or content, e.g. vending or licensing of copyrighted material protection in video systems or pay television H04N7/16 ; Digital rights management [DRM]
• CPC Class Codes: G06F 21/6236 between heterogeneous systems
• CPC Class Codes: G06F 2213/0038 System on Chip
• CPC Class Codes: G06F 2216/01 Automatic library building
• CPC Class Codes: G06F 2221/2113 Multi-level security, e.g. mandatory access control
• CPC Class Codes: G06F 2221/2137 Time limited access, e.g. to a computer or data
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 20/1235 with control of digital rights management [DRM]
• CPC Class Codes: G06Q 20/386 using messaging services or messaging apps using mobile network messaging services for payment, e.g. SMS G06Q20/3255
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G11B 20/00086 Circuits for prevention of unauthorised reproduction or copying, e.g. piracy indicating unauthorised use of record carriers in general G11B23/28; scrambling for television signal recording H04N5/913; network architectures or network protocols for network security H04L63/00; cryptographic mechanisms or cryptographic arrangements for secret or secure communication H04L9/00
• CPC Class Codes: G11B 27/105 of operating discs
• CPC Class Codes: G11B 27/34 : Indicating arrangements indicating means incorporated in magazine or cassette G11B23/046 and G11B23/0875; indicating measured values in general G01D
• CPC Class Codes: H04L 12/1822 : Conducting the conference, e.g. admission, detection, selection or grouping of participants, correlating users to one or more conference sessions, prioritising transmission
• CPC Class Codes: H04L 2463/101 : applying security measures for digital rights management data processing systems or methods, specially adapted for commerce, e.g. marketing, shopping, billing, auctions or e-commerce G06Q30/00
• CPC Class Codes: H04L 51/04 : Real-time or near real-time messaging, e.g. instant messaging [IM]
• CPC Class Codes: H04L 63/0263 : Rule management
• CPC Class Codes: H04L 63/101 : Access control lists [ACL]
• CPC Class Codes: H04L 63/105 : Multiple levels of security
• CPC Class Codes: H04L 65/1101 : Session protocols
• CPC Class Codes: H04L 65/612 : for unicast
• CPC Class Codes: H04L 67/06 : specially adapted for file transfer, e.g. file transfer protocol [FTP]
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04L 67/34 : involving the movement of software or configuration parameters network booting or remote initial program loading [RIPL] G06F9/4416
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/62 : Establishing a time schedule for servicing the requests
• CPC Class Codes: H04L 67/63 : Routing a service request depending on the request content or context
• CPC Class Codes: H04N 21/2541 : Rights Management protecting software against unauthorised usage in a vending or licensing environment G06F21/10; security in data switching network management H04L41/28; security management or policies for network security H04L63/20; access security in wireless networks H04W12/08
• CPC Class Codes: H04N 21/4126 : The peripheral being portable, e.g. PDAs or mobile phones
• CPC Class Codes: H04N 21/41407 : embedded in a portable device, e.g. video client on a mobile phone, PDA, laptop constructional details of equipment or arrangements specially adapted for portable computer application G06F1/1626; arrangements specially adapted for mobile receivers in broadcast systems H04H20/57
• CPC Class Codes: H04N 21/4331 : Caching operations, e.g. of an advertisement for later insertion during playback
• CPC Class Codes: H04N 21/4622 : Retrieving content or additional data from different sources, e.g. from a broadcast channel and the Internet web site content organization and management for information retrieval from the Internet G06F16/958; transmission by internet of broadcast information H04H60/82; stock exchange data over packet-switching network H04L12/1804; push services including data channel over packet-switching network H04L12/1859
• CPC Class Codes: H04N 21/4627 : Rights management associated to the content security in data switching network management H04L41/28; security management or policies for network security H04L63/20; access security in wireless networks H04W12/08
• CPC Class Codes: H04N 21/47214 : for content reservation or setting reminders; for requesting event notification, e.g. of sport results or stock market stock exchange data over packet-switching network H04L12/1804; push services over packet-switching network H04L12/1859; notification of incoming messages in packet switching networks H04L51/224
• CPC Class Codes: H04N 21/4788 : communicating with other users, e.g. chatting arrangements for providing for computer conferences, e.g. chat rooms, to substation in data switching networks H04L12/1813; distributed application using peer-to-peer [P2P] networks H04L67/104
• CPC Class Codes: H04N 21/4825 : using a list of items to be played back in a given order, e.g. playlists
• CPC Class Codes: H04N 21/658 : Transmission by the client directed to the server
• CPC Class Codes: H04N 21/8113 : comprising music, e.g. song in MP3 format
• CPC Class Codes: H04N 21/8355 : involving usage data, e.g. number of copies or viewings allowed
• CPC Class Codes: H04N 7/17318 : Direct or substantially direct transmission and handling of requests
• CPC Class Codes: Y10S 707/913 : Multimedia

Abstract

A system and method of generating a playlist of affinity related media files using affinity relationship data. In one aspect the relationship affinity data is based upon a user rating score obtained from a population of user'"'"'s ratings associated with media file attributes. In one aspect, a media file attribute which can include an artist, album, title, and genre information associated with a media file is received from a user, indicating the user'"'"'s desire to create an affinity playlist of media files having an affinity relationship based upon the selected media file attribute.

Claims

1. A method of generating a playlist of affinity related media files comprising:

receiving from a user belonging to a population of users in a media service, a selected media file attribute of a plurality of media file attributes, each of said plurality of attributes associated with a media file and comprising at least album, artist, title and genre information related to said media file, wherein receiving said selected media file attribute represents said user'"'"'s desire to create an affinity playlist of media files having an affinity relationship based upon said selected media file attribute;

accessing affinity relationship data for generating affinity relationships, said affinity relationship data being based upon a user rating score obtained from said population of users'"'"' ratings associated with media file attributes, said rating score used to create affinity relationships among media files by determining which media file attributes have a user rating score that is equal to or greater than a predetermined rating threshold; and

assembling a playlist of media file identifiers, said playlist comprising a media file identifier associated with a playlist media file selected for said playlist by virtue of having a media file attribute that has an affinity relationship with said selected media file attribute but that is not said selected media file attribute.

2. The method of claim 1 wherein said user rating score is based on a scale having a value between 0 and 100, wherein a value of 100 represents the highest rating for a media file attribute.

3. The method of claim 1 wherein said user rating score is based on a scale having a value between 0 and 100, wherein a predetermined value within said scale represents the predetermined rating threshold for those media files that are considered liked by a user.

4. The method of claim 3 wherein said predetermined value comprises the value of 70.

5. The method of claim 1 wherein said user rating score is based on a scale having a value between 1 and 5, wherein a value of 5 represent the highest rating for a media file attribute.

6. The method of claim 1 further comprising sending said playlist of media file identifiers to be experienced by said user.

7. The method of claim 1 further comprising sending said playlist to a media player utilized by said user.

8. The method of claim 1 wherein said media service is located on the internet.

9. The method of claim 1 wherein said media file identifier comprises a pointer.

10. The method of claim 1 wherein said media file identifier comprises a universal resource locator.

11. The method of claim 1 wherein said user is located a local processor.

12. The method of claim 1 wherein said media files comprise audio files.

13. The method of claim 1 wherein said media files comprise video files.

14. The method of claim 1 wherein said affinity relationship data for a first media file attribute associated with a media file is compiled based on the formula (AB/A)×

100, wherein A is the number of users of said population whose rating score associated with said first attribute is equal to or greater than said predetermined threshold, B is the number of users of said population whose rating score associated with a second attribute associated with another media file is equal to or greater than said predetermined threshold, and AB is the number of users of said population whose rating score for each of said first attribute and said second attribute is file is equal to or greater than said predetermined threshold.

15. The method of claim 14 wherein said first media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said media file.

16. The method of claim 14 wherein said second media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said another media file.

17. The method of claim 1 wherein said affinity relationship data for a first media file attribute associated with a media file is compiled based on the formula (AB/A)÷

(B/N), wherein A is the number of users of said population whose rating score associated with said first attribute is equal to or greater than said predetermined threshold, B is the number of users of said population whose rating score associated with a second media file attribute associated with another media file is equal to or greater than said predetermined threshold, and AB is the number of users of said population whose rating score for each of said first attribute and said second attribute is file is equal to or greater than said predetermined threshold, and N is the total number of users of said population.

18. The method of claim 17 wherein said first media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said media file.

19. The method of claim 17 wherein said second media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said another media file.

20. The method of claim 1 further comprising receiving selected media file obscurity criteria from said user;

and accessing affinity relationship data to identify media files that match said selected obscurity criteria.

21. The method of claim 20 wherein said obscurity criteria is based on information received from said population of users related to a media file'"'"'s popularity.

22. A system for generating a playlist of affinity related media files comprising one or more servers configured to:

receive from a user belonging to a population of users in a media service, a selected media file attribute of a plurality of media file attributes, each of said plurality of attributes associated with a media file and comprising at least album, artist, title and genre information related to said media file, wherein receiving said selected media file attribute represents said user'"'"'s desire to create an affinity playlist of media files having an affinity relationship based upon said selected media file attribute;

access affinity relationship data for generating affinity relationships, said affinity relationship data being based upon a user rating score obtained from said population of users'"'"' ratings associated with media file attributes, said rating score used to create affinity relationships among media files by determining which media file attributes have a user rating score that is equal to or greater than a predetermined rating threshold; and

assemble a playlist of media file identifiers, said playlist comprising a media file identifier associated with a playlist media file selected for said playlist by virtue of having a media file attribute that has an affinity relationship with said selected media file attribute but that is not said selected media file attribute.

23. The system of claim 22 wherein said user rating score is based on a scale having a value between 0 and 100, wherein a value of 100 represents the highest rating for a media file attribute.

24. The system of claim 22 wherein said user rating score is based on a scale having a value between 0 and 100, wherein a predetermined value within said scale represents the predetermined rating threshold for those media files that are considered liked by a user.

25. The system of claim 24 wherein said predetermined value comprises the value of 70.

26. The system of claim 22 wherein said user rating score is based on a scale having a value between 1 and 5, wherein a value of 5 represents the highest rating for a media file attribute.

27. The system of claim 22 further comprising said one or more servers configured to send said playlist of media file identifiers to be experienced by said user.

28. The system of claim 22 further comprising said one or more servers configured to send said playlist to a media player utilized by said user.

29. The system of claim 22 wherein said media service is located on the internet.

30. The system of claim 22 wherein said media file identifier comprises a pointer.

31. The system of claim 22 wherein said media file identifier comprises a universal resource locator.

32. The system of claim 22 wherein said user is located a local processor.

33. The system of claim 22 wherein said media files comprise audio files.

34. The system of claim 22 wherein said media files comprise video files.

35. The system of claim 22 wherein said affinity relationship data for a first media file attribute associated with a media file is compiled based on the formula (AB/A)×

100, wherein A is the number of users of said population whose rating score associated with said first attribute is equal to or greater than said predetermined threshold, B is the number of users of said population whose rating score associated with a second attribute associated with another media file is equal to or greater than said predetermined threshold, and AB is the number of users of said population whose rating score for each of said first attribute and said second attribute is file is equal to or greater than said predetermined threshold.

36. The system of claim 35 wherein said first media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said media file.

37. The system of claim 35 wherein said second media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said another media file.

38. The system of claim 22 wherein said affinity relationship data for a first media file attribute associated with a media file is compiled based on the formula (AB/A)÷

(B/N), wherein A is the number of users of said population whose rating score associated with said first attribute is equal to or greater than said predetermined threshold, B is the number of users of said population whose rating score associated with a second media file attribute associated with another media file is equal to or greater than said predetermined threshold, and AB is the number of users of said population whose rating score for each of said first attribute and said second attribute is file is equal to or greater than said predetermined threshold, and N is the total number of users of said population.

39. The system of claim 38 wherein said first media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said media file.

40. The system of claim 38 wherein said second media file attribute is selected from the group consisting of an album, artist, title, and genre information related to said another media file.

41. The system of claim 22 further comprising said one or more servers configured to receive selected media file obscurity criteria from said user;

and accessing affinity relationship data to identify media files that match said selected obscurity criteria.

42. The system of claim 41 wherein said obscurity criteria is based on information received from said population of users related to a media file'"'"'s popularity.