INFORMATION EXTRACTION BY SOCIAL MEDIA ANALYSISGiuseppe Amato – ISTI-CNR (MIR-NeMIS)

What information can be extracted?

Very high value in multimedia content Security

Identify risks or provide information Quasi real-time news

Get information from people witnessing an event in real time

Marketing What are the new emerging trends?

Entertainment People spend a lot of time with on-line media. What are

they looking for? Human behaviour analysis

What do people do in this moment.

Boston bombing

Rome – Feyenoord FCsupporter riots

Security / quasi real-time news

Market trends

-Entertainment-Behaviour-Events

Challenges

Effectiveness Extract information

relevant pertinent useful

Scalability Keep track and handle a continuous flow of

media Billion images and videos

Our Skill

Multimedia information retrieval on very large scale Prototypes using 100 millions images

Similarity search on very large scale Searching by similarity on faces, images,

objects, audios, etc. Real time image matching on very

limited resources Prototypes recognizing in real-time around

1000 images on mobile phones Image content classification/recognition

Research group

Permanent Giuseppe Amato Fausto Rabitti Pasquale Savino Claudio Gennaro Fabrizio Falchi Franca Debole

Temporary Costantino

Thanos (AS) Fraco A. Cardillo

(PD) Claudio Vairo (PD) Paolo Bolettieri

(TS)

Fundings and Projects

National 210k€ (120k€ soBigData related) /year

Inter. 1380k€ (190€ soBigData related) /year

On going soBigData related projects: FP7 STREP - RUBICON (2011-2014) CIP-ICT-PSP - EAGLE (2013-2016) PON – DiCET (2013-2014) POR CREO - SECURE (2013-2014),

Research aim

Study and develop techniques to Analyze Aggregate Annotate Make searchable

user generated multimedia content available on social networks