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"ACM SIGCHI General Interest Announcements (Mailing List)" <[log in to unmask]>
Wed, 4 Mar 2020 16:33:27 +0900
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Intelligent Cross Data Analytics and Retrieval Workshop (ICDAR) 2020
8 June 2020 | Dublin, Ireland  
(co-located with ICMR 2020)

The deadline will be extended to 20th March, 2020.

We'd like to invite you to submit your papers for the ICDAR workshop to be held on 8 
June 2020 in Dubline, Ireland.

Currently, people can collect data from themselves and their surrounding 
environment quickly due to the exponential development of sensors and 
communication technologies and social networks. The ability to collect 
such data opens the new opportunity to understand better the association 
between human beings and the properties of the surrounding environment. 
These associations can be utilized for intelligence, planning, 
controlling, retrieval, and decision making efficiently and effectively 
by governments, industries, and citizens. Wearable sensors, lifelog 
cameras, and social networks can report peopleĒs health, activities, and 
behaviors by the first-view perspective while surrounding sensors, 
social networks interaction, and third-party data can give the third-
view perspective of how their society activities look like. Several 
investigations have been done to deal with each perspective, but few 
investigations focus on how to analyze and retrieve cross-data come from 
different perspectives to bring better benefits to human beings. The 
target of the workshop is to attract researchers to work on the 
intelligent cross-data analysis and retrieval to bring the smart 
sustainable society to human beings. The domain of the research can vary 
from wellbeing, disaster prevention & mitigation, mobility, to food 
computing, to name a few.

The goal of the workshop is to attract researchers and experts in the 
areas of multimedia information retrieval, machine learning, AI, data 
science, event-based processing and analysis, multimodal multimedia 
content analysis, lifelog data analysis, urban computing, environmental 
science, and atmospheric science to tackle the intelligent cross-data 
analysis issue.

A. Submission Guidelines
  All papers must be original and not simultaneously submitted to 
another journal or conference. All papers must be formatted according to 
the ACM proceedings style. All technical content including the main text,
 figures, tables, and reference should be included within 6 pages.

B. List of Topics
- Event-based cross-data retrieval
- Data mining and AI technology to discover and predict spatial-temporal
-semantic correlations between cross-data.
- Complex event processing for linking sensors data from individuals, 
regions, to broad areas dynamically.
- Transfer Learning from one region to another region to construct or 
customize similar analysis and prediction of events using locally-
collected data effectively and efficiently.
- Hypotheses Development of the associations within the heterogeneous 
data contributes towards building good multimodal models that make it 
possible to understand the impact of the surrounding environment on 
human beings at the local and individual scale.
- Realization of a prosperous and independent region in which people and 
nature coexist.
- Applications leverage intelligent cross-data analysis for a particular 
- Cross-datasets for Repeatable Experimentation.

C. Organizers
- Minh-Son Dao (NICT, Japan)
- Morten Fjeld (University of Bergen, Norway)

D. Programming committee
- Uraz Yavanoglu (Gazi University, Turkey)
- Filip Biljecki (National University of Singapore)
- Mianxiang Dong (Muroran Institute of Technology, Japan)

E. Publication
  ICDAR 2020 proceedings will be published in ICMR 2020 by ACM 

  Excellent papers are encouraged to submit to journals or a special 
issue that will be organized by the organizers.

F. Venue
  The conference will be held in Radisson Blu Hotel, Golden Lane, in 
DublinĒs city center.

G. Contact
  All questions about submissions should be emailed to [log in to unmask]
Minh-Son DAO, Ph.D
Senior Researcher
Big Data Analytics Laboratory
National Institute of Information and Communications Technology (NICT)
4-2-1, Nukui-Kitamachi, Koganei, Tokyo 184-8795, Japan
Tel: +81 42-327-7356

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