REAL-TIME VISUALIZATION OF USER CONSUMPTION OF MEDIA ITEMS

• US 20100088273A1
• Filed: 10/02/2009
• Published: 04/08/2010
• Est. Priority Date: 10/02/2008
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Strands Incorporated (CRIBIS Holding SRL)
• Inventors: Donaldson, Justin
• Granted Patent: US 8,332,406 B2
• Time in Patent Office: Days
• US Class Current: 707/609
• 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 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 displaying a visualization of the event, wherein addition of graphical symbols to the visualization display is responsive to the arrangement of the consumption data in the data structure.

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

associating one or more counters with the consumption data in the data structure;

incrementing the counters upon adding the consumption data to the data structure;

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

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

adding one or more graphical symbols to the visualization display responsive to the arrangement of the consumption data in the data structure, wherein the graphical symbols are positioned in the display according to a force-direct placement method;

removing the consumption data from the data structure when an associated counter decrements to zero; and

removing graphical symbols from the visualization display upon removal of the corresponding consumption data from the data structure.

3. The computer implemented method of claim 2, wherein adding one or more graphical symbols to the visualization display further comprises adding nodes to the visualization display for consumption data that is not currently represented in the visualization display.

4. The computer implemented method of claim 3, wherein adding graphical symbols to the visualization display comprises connecting two correlated nodes by adding, an edge between the two correlated nodes, wherein each of the correlated nodes represents consumption data that is correlated in the data structure.

5. The computer implemented method of claim 4, wherein adding an edge further comprises rendering a graphical connector line between a first node and a second node according to the force-direct placement method and wherein the first node and the second node exhibit a simulated attraction force with respect to one another.

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

7. The computer implemented method of claim 1, wherein the real-time computer mediated user consumption data corresponds to user listening behavior.

8. The computer implemented method of claim 7, wherein the data structure is a series of hash tables for identifying and tracking;

musical artists, users, music tracks played, user last tracks played, correlations between different artists with respect to users'"'"' listening activity and temporal context of the users'"'"' listening activity.

9. The computer implemented method of claim 4, further comprising storing edge data in the data structure to identify neighboring nodes for each correlated node in the visualization display.

10. The computer implemented method of claim 9, wherein the edge data is configured for incrementing and decrementing counters associated with the edge data in the data structure.

11. 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.

12. A tangible machine-readable storage medium comprising instructions which, when executed, cause the machine to:

access a series of events comprising real-time consumption data, wherein the events are associated with a user and a unique sequential identifier;

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

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

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

increment counters in the data structure associated with the arranged real-time consumption data upon addition of the real-time consumption data to the data structure;

add graphical representations of the arranged real-time consumption data to a visualization display according to the arrangement of the real-time consumption data in the data structure;

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

decrement counters in the data structure associated with the arranged real-time consumption data upon removal of the old event from the event stack wherein the old event corresponds to the arranged real-time consumption data to be decremented.

13. The tangible machine-readable storage medium of claim 12 comprising further instructions which, when executed, cause the machine to add one or more nodes to the visualization display representing the arranged real-time consumption data wherein the nodes display graphics corresponding to the arranged real-time consumption data.

14. The tangible machine-readable storage medium of claim 13 comprising further instructions which, when executed, cause the machine to identify related nodes and add graphical connectors between the related nodes according to the arranged real-time consumption data.

15. The tangible machine-readable storage medium of claim 12 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.

16. The tangible machine-readable storage medium of claim 12 comprising further instructions which, when executed, cause the machine to remove arranged real-time consumption data from the data structure when the counter associated with the arranged real-time consumption data is decremented to zero.

17. The tangible machine-readable storage medium of claim 12, wherein the data structure is a series of hash tables.

18. The tangible machine-readable storage medium of claim 12, wherein the data structure correlates arranged real-time consumption data 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.

19. The tangible machine-readable storage medium of claim 12 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.