Real-time visualization of user consumption of media items

• US 8,332,406 B2
• Filed: 10/02/2009
• Issued: 12/11/2012
• Est. Priority Date: 10/02/2008
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Donaldson, Justin
• Primary Examiner(s): Pulliam, Christyann
• Assistant Examiner(s): Mahmood, Rezwanul
• Application Number:
  US12/572,984
• Publication Number:
  US 20100088273A1
• Time in Patent Office: 1,166 Days
• Field of Search: 707/609, 707/802, 707/711, 707/736, 707/754, 707/758, 707/776, 707/913
• US Class Current: 707/736
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

A computer implemented method for displaying real-time computer mediated user consumption data, comprising: accessing consumption data corresponding to real-time computer mediated user consumption behavior; parsing the consumption data to identify one or more events comprising one or more instances of consumption data and wherein each event is associated with a user; adding the events to an event stack comprising a predetermined stack limit; and storing the consumption data for each event in a data structure configured to correlate related consumption data and provide a temporal context to the stored consumption data wherein addition of graphical symbols to a visualization display is responsive to the arrangement of the consumption data in the data structure.

Claims

1. A computer implemented method for displaying real-time computer mediated user consumption data, comprising:

accessing media item listening behavior corresponding to real-time computer mediated user media item listening behavior;

parsing the media item listening behavior to identify one or more play events comprising one or more instances of media item listening behavior and wherein each play event is associated with a user, and wherein play events comprise instances of media items associated with the user being purchased, played, replayed, tagged, and skipped;

adding the play events to an event stack comprising a predetermined stack limit;

storing the media item listening behavior for each play event in a data structure comprising a plurality of hash tables for identifying and tracking media item attributes including;

artists, users, tracks played, user last tracks played, correlations between different artists with respect to users'"'"' listening activity and temporal context of the users'"'"' listening activity, the data structure configured to correlate related media item listening behavior and to provide a temporal context to the stored media item listening behavior;

displaying a visualization of the play events responsive to the arrangement of the media item listening behavior in the data structure, wherein displaying comprises;

adding a plurality of nodes representing artists and a plurality of edges representing consecutive play events of the same artist, each edge connecting a first node of the plurality of nodes to a second node of the plurality of nodes correlated to the first node, each of the plurality of nodes assigned a velocity, a position, a net force, and an identifier associated with one or more media items, and each of the plurality of edges assigned a net spring force;

applying a damping factor; and

repeatedly updating the position of each of the plurality of nodes based at least on the net force and the velocity assigned to each of the plurality of nodes, the net spring force assigned to each of the plurality of edges, and the damping factor until the position for each of the plurality of nodes reaches an equilibrium; and

updating the visualization display responsive to each change in the artists, users, tracks played, user last tracks played, correlations between different artists with respect to users'"'"' listening activity and temporal context of the users'"'"' listening activity.

2. The computer implemented method of claim 1, further comprising:

associating one or more counters with the media item listening behavior in the data structure;

incrementing the counters upon adding the media item listening behavior to the data structure;

identifying and removing an oldest play event from the event stack after the predetermined stack limit is exceeded;

decrementing the counters responsive to removing the oldest play event from the event stack; and

removing the media item listening behavior from the data structure when an associated counter decrements to zero.

3. The computer implemented method of claim 2, wherein removing the oldest play event from the event stack further comprises selectively pruning media item listening behavior from the data structure by decrementing the counters for media item listening behavior associated with the oldest play event and removing media item listening behavior from the data structure corresponding to counters that are decremented to zero.

4. The computer implemented method of claim 1, wherein the edge data is configured for incrementing and decrementing counters associated with the edge data in the data structure.

5. The computer implemented method of claim 1, further comprising:

extracting and validating meta-data related to consumption data for a particular event;

storing the meta-data in the data structure in association with the related consumption data; and

periodically updating the meta-data.

6. A non-transitory machine-readable storage medium comprising instructions which, when executed, cause the machine to:

access a series of play events comprising real-time media item listening behavior, wherein the play events are associated with a user and a unique sequential identifier, wherein play events comprise instances of media items associated with the user being purchased, played, replayed, tagged, and skipped;

compare the play event identifiers to previously retrieved play event identifiers to determine whether the play events are new;

store one or more new play events in an event stack wherein the event stack has a predetermine stack limit;

arrange real-time media item listening behavior corresponding to the new play events in one or more data structures, wherein the data structures are configured to correlate real-time media item listening behavior and to maintain a temporal context for real-time media item listening behavior;

increment counters in the data structure associated with the arranged real-time media item listening behavior upon addition of the real-time media item listening behavior to the data structure, wherein the data structure comprises a plurality of hash tables for identifying and tracking media item attributes including;

artist, users, tracks played, user last track played, correlations between different artists with respect to users'"'"' listening activity and temporal context of the users'"'"' listening activity;

display a visualization of the arranged real-time media item listening behavior responsive to the arrangement of the real-time media item listening behavior in the data structure, wherein displaying comprises;

adding a plurality of nodes representing artists and a plurality of edges representing consecutive play events of the same artist, each edge connecting a first node of the plurality of nodes to a second node of the plurality of nodes correlated to the first node, each of the plurality of nodes assigned a velocity, a position, a net force, and an identifier associated with one or more media items, and each of the plurality of edges assigned a net spring force;

applying a damping factor; and

repeatedly updating the position of each of the plurality of nodes based at least on the net force and the velocity assigned to each of the plurality of nodes, the net spring force assigned to each of the plurality of edges, and the damping factor until the position for each of the plurality of nodes reaches an equilibrium;

identify and remove an old event from the event stack responsive to the event stack exceeding the predetermined stack limit;

decrement counters in the data structure associated with the arranged real-time media item listening behavior upon removal of the old event from the event stack wherein the old event corresponds to the arranged real-time media item listening behavior that is scheduled to be decremented; and

update the visualization display responsive to each change in the artists, users, tracks played, user last tracks played, correlations between different artists with respect to users'"'"' listening activity and temporal context of the users'"'"' listening activity.

7. The tangible machine-readable storage medium of claim 6 comprising further instructions which, when executed, cause the machine to determine the oldest event in the stack according to a first in first out method.

8. The tangible machine-readable storage medium of claim 6 comprising further instructions which, when executed, cause the machine to remove arranged real-time media item listening behavior from the data structure when the counter associated with the arranged real-time media item listening behavior is decremented to zero.

9. The tangible machine-readable storage medium of claim 6, wherein the data structure correlates arranged real-time media item listening behavior and stores an indication of the correlation as a separate entry in the data structure and wherein the correlation entry is associated with a counters for incrementing and decrementing.

10. The tangible machine-readable storage medium of claim 6 comprising instructions which, when executed, further cause the machine to:

validate meta-data associated with the new event;

store the meta-data in the data structure; and

update the meta-data as additional new events are accessed comprising corresponding meta-data.