Connectionists: Advances in segmentation of data streams - Deadline 2020-01-25

[Stefano Rovetta]

Second announcement -- DEADLINE EXTENDED TO JANUARY 25, 2020

**** Advances in segmentation of data streams ****

SPECIAL SESSION @ IEEE EAIS 2020

https://sites.google.com/view/eais2020/conference/special-sessions/advances-in-segmentation-of-data-streams
http://eais2020.di.uniba.it/


Due to the growing presence of ubiquitous data sources and the 
requirement for shorter and shorter response times, data streaming is 
steadily becoming the key technology to modern information processing, 
and this trend is bringing up new challenges. As data analysis moves 
from simple organisation and classification to content understanding, 
for instance, the meaning of segmentation becomes more and more complex 
to define. When does a concept start within a text, and where does it 
stop? Which objects are interesting in a video, and where are they 
located? When does a machine start to show a degradation process that 
will lead to a need for maintenance? Where does a spoken text start to 
show a certain mood?

This special session aims to explore current topics in data stream 
understanding, with emphasis on segmentation, the process of identifying 
meaningful entities within a stream of data. This is often an 
ill-defined goal, where object boundaries are uncertain  and object 
definition is unclear, subjective, or not given in advance. 
Notwithstanding this, the task emerges everywhere and can be 
instantiated in a vast number of vertical application areas, including 
just as an indication:

- Natural language processing/understanding
- The Internet of Things (IoT) and sensor networks
- Industrial process control
- Gesture recognition in artificial vision
- Speech analysis and synthesis
- Road traffic monitoring and control (Smart City)
- Predictive maintenance (Industry 4.0)
- Health monitoring
- Web traffic analysis and user profiling
- Extreme climatic event forecasting
- Sentiment analysis in marketing
- Automatic video scene identification

Contributions on any of these subject areas, as well as other, are 
sought for this special session, as long as they focus on the intended 
theme. Diversity is encouraged, as it promotes cross-fertilisation.



Special session organizers:

Stefano Rovetta
University of Genova

Zied Mnasri
zied.mnasri at enit.utm.tn
University of Tunis El Manar, Tunis, Tunisia
and University of Genova, Italy