Social Media Event Detection and Content-Based Retrieval

• US 20150227840A1
• Filed: 04/22/2015
• Published: 08/13/2015
• Est. Priority Date: 09/24/2012
• Status: Active Grant

• Current Assignee: AirBNB Incorporated
• Original Assignee: International Business Machines Corporation
• Inventors: Codella, Noel C., Natsev, Apostol, Smith, John R.
• Granted Patent: US 10,032,113 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/58 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/583 using metadata automatically derived from the content
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 20/10 using kernel methods, e.g. support vector machines [SVM]
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks

Abstract

Techniques for detecting an event via social media content. A method includes obtaining multiple images from at least one social media source; extracting at least one visual semantic concept from the multiple images; differentiating an event semantic concept signal from a background semantic concept signal to detect an event in the multiple images; retrieving one or more images associated with the event semantic concept signal; grouping the one or more images associated with the event semantic concept signal; annotating the group of one or more images with user feedback; and displaying the annotated group of one or more images as a visual description of the detected event.

Claims

1. A method for detecting an event via social media content, the method comprising:

obtaining multiple images from at least one social media source;

extracting at least one visual semantic concept from the multiple images;

differentiating an event semantic concept signal from a background semantic concept signal to detect an event in the multiple images;

retrieving one or more images associated with the event semantic concept signal;

grouping the one or more images associated with the event semantic concept signal;

annotating the group of one or more images with user feedback; and

displaying the annotated group of one or more images as a visual description of the detected event;

wherein at least one of the steps is carried out by a computer device.

2. The method of claim 1, wherein said differentiating is based on comparing signal strength of each of the at least one extracted visual semantic concept to a predetermined outlier threshold.

3. The method of claim 1, comprising:

overlaying images annotated with a global position system (GPS) function onto a map to provide a geo-spatial representation of the event.

4. The method of claim 1, wherein the multiple images from at least one social media source comprise images derived from photo input.

5. The method of claim 4, wherein the photo input comprises user-posted images on at least one social media source.

6. The method of claim 1, wherein the multiple images from at least one social media source comprise images derived from video input.

7. The method of claim 6, wherein the video input comprises user-posted videos on at least one social media source.

8. The method of claim 1, wherein said obtaining comprises streaming multiple images from the at least one social media source in real-time.

9. The method of claim 1, wherein the at least one visual semantic concept characterizes an event.

10. The method of claim 1, wherein said differentiating comprises measuring a mean and standard deviation of each semantic concept over a user-specified background time period.

11. The method of claim 1, wherein said differentiating comprises using an interactive machine learning algorithm.

12. The method of claim 11, comprising:

assessing which of the multiple images contributed most prominently to event detection as event-related.

13. The method of claim 1, wherein said differentiating comprises performing a statistical analysis to compute a probability that an event has occurred.

14. The method of claim 1, comprising:

measuring the signal of each semantic concept over time.

15. The method of claim 1, comprising:

identifying one or more semantic concept signal peaks that signify a real-time event.

16. The method of claim 1, comprising:

retrieving one or more additional images that are relevant to a detected event.

17. The method of claim 1, comprising:

monitoring semantics of images uploaded to one or more social media websites over a specified time period.

18. The method of claim 17, comprising:

streaming images to a parallel system which applies a set of generated semantic models to the images in real-time.

19. The method of claim 1, comprising:

specifying a background time period and an event time period.