EVENT RECOMMENDATION SYSTEM AND METHOD

• US 20160275170A1
• Filed: 03/20/2015
• Published: 09/22/2016
• Est. Priority Date: 03/20/2015
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: BUFE, JOHN P., Kummamuru, Krishna, Krishnamurthy, Lakshminarayanan, Pal, Manojkumar
• Application Number:
  US14/664,161
• Publication Number:
  US 20160275170A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: H04W 4/08 User group management
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

A method, computer program product, and computer system for identifying data associated with an event. A recommendation is provided to at least the event based upon, at least in part, at least one of a character of the event determined based upon, at least in part, the data associated with the event, and a personality of a real-time crowd at the event determined based upon, at least in part, the data associated with the event.

Claims

1-7. -7. (canceled)

8. A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

identifying data associated with an event; and

providing a recommendation to at least the event based upon, at least in part, at least one of,

a character of the event determined based upon, at least in part, the data associated with the event, and

a personality of a real-time crowd at the event determined based upon, at least in part, the data associated with the event.

9. The computer program product of claim 8 wherein providing the recommendation to at least the event includes clustering one or more events that are similar to the event based upon one or more preferences.

10. The computer program product of claim 8 wherein identifying the data associated with the event includes analyzing social media data.

11. The computer program product of claim 8 wherein determining the character of the event includes:

separating user reviews into a positive group of users and a negative group of users;

generating one or more personality profiles for at least a portion of the positive group of users and the negative group of users;

generating a group personality profile for the positive group of users and the negative group of users using the one or more personality profiles; and

determining one or more distinguishing features between the positive group of users and the negative group of users.

12. The computer program product of claim 8 wherein determining the personality of the real-time crowd at the event includes:

generating a personality profile for at least a portion of users at the event; and

generating a group personality profile from the personality profile.

13. The computer program product of claim 9 wherein clustering the one or more events includes determining a similarity metric for the event and the one or more events, wherein at least a portion of the one or more events above a similarity threshold are clustered.

14. The computer program product of claim 9 wherein the one or more preferences include at least one of distance and transportation method.

15. A computing system including a processor and a memory configured to perform operations comprising:

identifying data associated with an event; and

providing a recommendation to at least the event based upon, at least in part, at least one of,

a character of the event determined based upon, at least in part, the data associated with the event, and

a personality of a real-time crowd at the event determined based upon, at least in part, the data associated with the event.

16. The computing system of claim 15 wherein providing the recommendation to at least the event includes clustering one or more events that are similar to the event based upon one or more preferences.

17. The computing system of claim 15 wherein identifying the data associated with the event includes analyzing social media data.

18. The computing system of claim 15 wherein determining the character of the event includes:

separating user reviews into a positive group of users and a negative group of users;

generating one or more personality profiles for at least a portion of the positive group of users and the negative group of users;

generating a group personality profile for the positive group of users and the negative group of users using the one or more personality profiles; and

determining one or more distinguishing features between the positive group of users and the negative group of users.

19. The computing system of claim 15 wherein determining the personality of the real-time crowd at the event includes:

generating a personality profile for at least a portion of users at the event; and

generating a group personality profile from the personality profile.

20. The computing system of claim 16 wherein clustering the one or more events includes determining a similarity metric for the event and the one or more events, wherein at least a portion of the one or more events above a similarity threshold are clustered.