GENERATING EXCITEMENT LEVELS FOR LIVE PERFORMANCES

• US 20140067939A1
• Filed: 08/31/2012
• Published: 03/06/2014
• Est. Priority Date: 08/31/2012
• Status: Active Grant

• Current Assignee: STATS LLC (Stats Holdings LLC)
• Original Assignee: Thuuz, Inc.
• Inventors: Packard, Warren Joseph, Barcklay, Robert John, Levin, Alan
• Granted Patent: US 9,060,210 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/25883 being end-user demographical data, e.g. age, family status or address arrangements for identifying locations of users in broadcast systems H04H60/52
• 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 21/26241 involving the time of distribution, e.g. the best time of the day for inserting an advertisement or airing a children program
• CPC Class Codes: H04N 21/2625 for delaying content or additional data distribution, e.g. because of an extended sport event
• CPC Class Codes: H04N 21/26603 for automatically generating descriptors from content, e.g. when it is not made available by its provider, using content analysis techniques
• CPC Class Codes: H04N 21/2668 Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063
• 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 21/4882 for displaying messages, e.g. warnings, reminders arrangements for providing short real-time information to substation in data switching networks H04L12/1895
• CPC Class Codes: H04N 21/8549 Creating video summaries, e.g. movie trailer retrieval in video databases by using presentations in form of a video summary G06F16/739

Abstract

A live performance is monitored by analyzing an input data stream comprising real-time updates related to the live performance. Different sets of excitement levels, excitement curves, alerts and teasers are generated based on the analysis and reported to a plurality of subscribers using any of a variety of mobile communication and/or computing devices.

Claims

1. A method for generating excitement levels for a live performance, comprising:

monitoring a live performance;

generating different sets of excitement levels for the live performance based on the monitoring, the different sets of excitement levels relate to different categories of subscribers; and

reporting the different sets of excitement levels to a plurality of subscribers.

2. The method of claim 1 further comprising:

generating different sets of excitement curves for the different categories of subscribers from the different sets of excitement levels, each excitement curve is a graph of a set of excitement levels over time, the reporting the different sets of excitement levels comprises reporting the excitement curves.

3. The method of claim 2 wherein generating the different sets of excitement curves comprises:

analyzing an input data stream comprising real-time updates related to the live performance; and

identifying one or more events of interest in the live performance, based on the analyzing.

4. The method of claim 3 wherein generating the different sets of excitement curves further comprises:

determining information for performance attributes related to the input data stream based on the analyzing;

computing different scores for each of the performance attributes in the input data stream for the different subscriber categories;

applying generic weights to each of the performance attributes for the different subscriber categories; and

generating the different sets of excitement levels for the live performance for the different subscriber categories based on a sum of the scores for each of the performance attributes and the generic attribute weights applied to each of the performance attributes.

5. The method of claim 3 wherein:

the generating the different sets of excitement curves comprises analyzing the input data stream over a first time-interval to generate different sets of final excitement levels related to the live performance over time, the first time interval is from a beginning of the live performance to a current time.

6. The method of claim 5 wherein:

the generating the different sets of excitement curves comprises analyzing the input data stream over a second time-interval to generate different sets of instantaneous excitement levels related to the live performance over time, the second time interval is from a time after the beginning of the live performance to a current time.

7. The method of claim 2 wherein:

the generating the different sets of excitement curves for the different categories of subscribers comprises generating an excitement curve for a home team fan, an excitement curve for a visiting team fan and an excitement curve for a neutral fan.

8. The method of claim 7 further comprising

excitement curve for a home team fan is reported to subscribers who have indicated a preference for the home team;

the excitement curve for a visiting team fan is reported to subscribers who have indicated a preference for the visiting team; and

the excitement curve for a neutral fan is reported to subscribers who have not indicated a preference for the home team or the visiting team.

9. The method of claim 1 wherein:

generating the different sets of excitement levels for the live performance comprises computing different sets of pre-excitement levels, for the different categories of subscribers.

10. The method of claim 1, wherein identifying one or more events of interest comprise identifying a nail-biter event in the live performance and reporting the nail-biter event to one or more of the subscribers.

11. A method for generating excitement levels for a live performance, comprising:

analyzing an input data stream comprising real-time updates related to the live performance;

identifying one or more events of interest in the live performance based on the analyzing;

deriving one or more performance attributes related to the input data stream; and

generating different sets of excitement levels for the live performance, based on the one or more performance attributes, for different subscriber categories such that a first set of excitement levels is generated for a first category of subscribers and a second set of excitement levels is generated for a second category of subscribers.

12. The method of claim 11 wherein generating the different sets of excitement levels for the live performance further comprises:

computing different scores for each of the performance attributes in the input data stream, for the different subscriber categories;

applying generic weights to each of the performance attributes for the different subscriber categories; and

generating the different sets of excitement levels for the live performance, for the different subscriber categories based on a sum of the scores for each of the performance attributes and the generic attribute weights applied to each of the performance attributes.

13. The method of claim 11, wherein the one or more performance attributes comprise at least one of a velocity attribute, a parity attribute, a novelty attribute, a momentum attribute and a context attribute related to the live performance.

14. The method of claim 11, further comprising:

generating different sets of excitement curves for the different categories of subscribers from the different sets of excitement levels, each excitement curve is a graph of a set of excitement levels over time.

15. The method of claim 14, further comprising:

reporting the different sets of excitement curves for the different categories of subscribers, to a plurality of subscribers in accordance with one or more subscriber preferences.

16. The method of claim 15, wherein:

reporting the different sets of excitement curves comprises reporting an excitement curve for a home team fan, an excitement curve for a visiting team fan and an excitement curve for a neutral fan related to the live performance.

17. The method of claim 15, wherein:

reporting the different sets of excitement curves comprises displaying different sets of watch-from-times related to the live performance for the different sets of excitement curves, the different sets of watch-from-times determined based on identifying different sets of peak excitement levels in the different excitement curves for the different subscriber categories.

18. One or more processor readable storage devices having processor readable code embodied on the processor readable storage devices, the processor readable code for programming one or more processors to perform a method comprising:

analyzing an input data stream comprising real-time updates related to the live performance;

identifying one or more events of interest in the live performance, based on the analyzing;

deriving one or more performance attributes related to the input data stream;

computing different scores for each of the performance attributes in the input data stream, for different subscriber categories;

applying generic weights to each of the performance attributes for the different subscriber categories; and

generating different sets of excitement levels for the live performance, for the different subscriber categories based on a sum of the scores for each of the performance attributes and the generic attribute weights applied to each of the performance attributes.

19. The one or more processor readable storage devices of claim 18 further comprising:

generating different sets of excitement curves for the different categories of subscribers from the different sets of excitement levels, each excitement curve is a graph of a set of excitement levels over time; and

reporting the different sets of excitement curves for the different categories of subscribers, in accordance with one or more subscriber preferences.

20. The one or more processor readable storage devices of claim 19 wherein generating the different sets of excitement curves comprises analyzing the input data stream over a first time-interval to generate different sets of final excitement levels related to the live performance over time.

21. A system for generating excitement levels for a plurality of live performances comprising:

one or more storage devices storing code;

a communication interface; and

one or more processors in communication with the one or more storage devices and the communication interface, the one or more processors configured to be in communication with a plurality of client devices via the communication interface based on the code, wherein the code configures the one or more processors to monitor a live performance, generate different sets of excitement levels for the live performance based on the monitoring and report the different sets of excitement levels to a plurality of subscribers, the different sets of excitement levels are for different categories of subscribers.

22. The system of claim 21 wherein:

the one or more processors generate different sets of excitement curves for the different categories of subscribers from the different sets of excitement levels, each excitement curve is a graph of a set of excitement levels over time.

23. The system of claim 21 wherein:

the one or more processors report the different sets of excitement curves to the plurality of subscribers, based on one or more subscriber preferences, on one or more display devices.