Systems and methods for prioritizing media files in a presentation device

• US 7,987,148 B2
• Filed: 05/20/2010
• Issued: 07/26/2011
• Est. Priority Date: 02/10/2006
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Strands Incorporated (CRIBIS Holding SRL)
• Inventors: Rowley, Craig, Caudevilla-Laliena, Guillermo, Yip, Andrew, Martin, Francisco, Del Ser Bartolome, David, McLaughlin, Matt, Hangartner, Rick, Shur, Jim
• Primary Examiner(s): Vincent; David R
• Assistant Examiner(s): Brown, Jr.; Nathan H
• Application Number:
  US12/783,739
• Publication Number:
  US 20100268680A1
• Time in Patent Office: 432 Days
• Field of Search: 706/46
• US Class Current: 706/46
• CPC Class Codes: G06F 16/4387 by the use of playlists
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G11B 27/034 on discs G11B27/036, G11B27/038 take precedence
• CPC Class Codes: G11B 27/036 Insert-editing
• CPC Class Codes: H04L 65/612 for unicast
• CPC Class Codes: H04L 67/1095 Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; 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 21/26258 for generating a list of items to be played back in a given order, e.g. playlist, or scheduling item distribution according to such list retrieval of multimedia data based on playlists G06F16/40
• CPC Class Codes: H04N 21/4335 Housekeeping operations, e.g. prioritizing content for deletion because of storage space restrictions storage management, e.g. defragmentation G06F3/0604; unloading stored programs G06F9/445; storage management in file systems G06F16/10; buffering arrangements in a network node or in an end terminal in packet networks H04L49/90
• CPC Class Codes: H04N 21/44204 Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched monitoring of user activities for profile generation for accessing a video database G06F16/739; protecting generic digital content where the protection is independent of the precise nature of the content G06F21/10; arrangements for monitoring the use made of the broadcast services in broadcast systems H04H60/31
• CPC Class Codes: H04N 21/6543 for forcing some client operations, e.g. recording remote booting in general G06F9/4416
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

Disclosed are embodiments of systems and methods for prioritizing mobile media player files by providing for the automated addition and/or deletion of media items for a mobile media player. In some embodiments, a statistical method may be provided for inferring which media items on a mobile media player should be deleted based on, for example, user taste data. In some embodiments, new media items may be loaded onto a user'"'"'s mobile media player by creating one or more playlists from a playlist builder. The playlist(s) may be created by using user taste data. Rankings may also be created to determine an order for deletion of the media items currently on a mobile media player and/or for addition of new media items to the device.

Claims

1. A computer-implemented method for the automated selection and loading of media items from a computer into a media presentation device, the method comprising:

at the time of initiating the removal and loading process,

receiving a media item current playlist from the media presentation device;

receiving current user taste data associated with a user of the media presentation device, the taste data reflecting recent use of the presentation device by the said user;

generating a recommended playlist responsive to the user taste data;

ranking the media items in the recommended playlist responsive to the user taste data;

determining an amount of memory storage space available on the media presentation device for storing new items; and

automatically removing as many media items from the media presentation device as necessary to free memory space sufficient to accommodate at least the highest ranked one of the ranked media items, wherein the media items are removed from the media presentation device in reaction to the current user'"'"'s taste data.

2. The method of claim 1 and further comprising:

selecting a media item from the recommended playlist;

deleting at least one item on the current playlist from the media presentation device to free memory space for the selected media item;

downloading the selected media item over the network into memory on the media presentation device; and

repeating said selecting, deleting and downloading steps until an available time for the auto-fill operation has expired.

3. The method of claim 2 and further comprising:

repeating said selecting, deleting and downloading steps until all the items on the current playlist have been deleted from the media presentation device.

4. The method of claim 2 and further comprising:

repeating said selecting, deleting and downloading steps until all the items on the recommended playlist have been downloaded into the media presentation device.

5. The method of claim 2 and further comprising:

repeating said selecting, deleting and downloading steps until a preselected number of media items from the recommended playlist have been downloaded into the media presentation device.

6. The method of claim 2 wherein the selecting and downloading steps include:

first selecting a highest ranked one of the recommended playlist media items; and

repeating said downloading step, in descending rank order of the media items, until the amount of memory storage space available on the media presentation device for storing new items is insufficient to add the next item.

7. The method of claim 2 and further comprising:

repeating said selecting, deleting and downloading steps until a user-selected amount of memory space is used in the media presentation device for storing new media items downloaded from the recommended playlist.

8. The method of claim 2 wherein removing media items from the current playlist comprises randomly selecting media items for removal.

9. The method of claim 2 wherein removing media items from the current playlist comprises:

ranking the media items in the current playlist based on compatibility with the user taste data used to generate the recommended playlist; and

selecting media items for removal in order of the said ranking, by sequentially removing the least compatible media items first and the most compatible media items last.

10. The method of claim 9, wherein the current user taste data comprises at least one of a metric indicative of the total number of plays for one or more media items in the current media item playlist, a metric indicative of a recent rate of plays for one or more media items in the current media item playlist, and a metric indicative of a recent rate of skips for one or more media items in the current media item playlist.

11. The method of claim 9, wherein said ranking media items in the current media item playlist in an order in which the media items are to be removed from the media presentation device includes ranking the media items stored on the mobile media presentation device according to a probability of deletion from the mobile media presentation device, responsive to implicit current user interest in retaining them, without explicit user input or user selections.

12. The method of claim 11 wherein the implicit user interest for each media item currently stored on the mobile media presentation device is quantified using a linear regression model responsive to a vector of selected covariates, wherein the covariates comprise measurable properties or metrics of the media items reflecting user taste that increase or decrease a probability of deleting the media item.

13. The method of claim 12 wherein the covariates are selected from a first class of metrics comprising 1) a total number of plays p(t) at any point in time, 2) a recent rate of plays r(t)=[p(t)−

p(t−

Δ

t)]/Δ

t, and

     3) a recent rate of skips s(t)=[q(t)−

q(t−

Δ

t)]/Δ

t, where q(t) is the number of times the listener has prematurely terminated playback of the item.

14. The method of claim 13 wherein the number of plays p(t) is normalized relative to a total number of plays P, (i.e., p(t)/P).

15. The method of claim 13 wherein the covariates are selected from a second class of metrics responsive to metadata similarity between one of the media items and a set of candidate new items j₁, j₂, . . . , j_m.

16. A computer-implemented method for the automated selection and loading of media items from a computer into a media presentation device, the method comprising:

accessing a current playlist associated with a media presentation device;

accessing explicitly specified user preferences associated with a selected media item on the playlist;

responsive to the user preferences, determining a designated time associated with the selected media item;

comparing the designated time to a current system time;

if the current system time is after the designated time, removing the selected media item from the playlist.

17. The method of claim 16 and further comprising:

selecting a new media item; and

automatically adding the selected new media item to the playlist for the media presentation device.

18. The method of claim 17 and further comprising:

automatically loading the selected new media item from the computer into the media presentation device for local storage.