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
http://www2.nict.go.jp/bidal/icdar_icmr2020/index.html 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
domain.
- 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
Proceedings.
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
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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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