Hi,
I send enclosed the CFP of MDAI2020 (sorry for multiple copies).
Deadline: March 7th.
vicenc
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CALL FOR PAPERS
17th International Conference on Modeling Decisions for Artificial Intelligence
MDAI 2020, Sant Cugat, Catalonia, Spain, September 2 - 4, 2020
http://www.mdai.cat/mdai2020
The conference is on different facets of decision processes in a broad sense.
This includes model building and all kind of mathematical tools for data
aggregation, information fusion, and decision making; tools to help decision in
data science problems (including e.g., statistical and machine learning
algorithms as well as data visualization tools); and algorithms for data
privacy and transparency-aware methods so that data processing processes and
decisions made from them are fair, transparent, explainable and avoid
unnecessary disclosure of sensitive information.
The MDAI conference includes tracks on the topics of (i) data science, (ii)
machine learning, (iii) data privacy, (iv) aggregation funcions, (v) human
decision making, and (vi) graphs and (social) networks. The conference has been
since 2004 a forum for researchers to discuss last results into these areas of
research.
Previous conferences were celebrated in Barcelona (2004, 2013), Tsukuba (2005),
Tarragona (2006), Kitakyushu (2007), Sabadell (2008), Awaji Island (2009),
Perpinya (2010), Changsha (2011), Girona (2012), Tokyo (2014), Skovde (2015),
St Julia de Loria (2016), Kitakyushu (2017), Mallorca (2018), Milan (2019).
MDAI is rated as a CORE B conference by the Computing Research and Education
Association of Australasia - CORE.
*Important Dates*
LNAI Submission deadline: March 7th, 2020
LNAI Acceptance notification: May, 2nd, 2020
Final version of LNAI accepted papers: May 22nd, 2020
Early registration: June 9th, 2020
Conference: September 2 - 4, 2020
*Submission and Publication*
Original technical contributions are sought. Contributions will be selected on
the basis of their quality. Papers should not exceed 12 pages in total (using
LNCS/LNAI style). Proceedings with accepted papers will be published in the
LNAI/LNCS series (Springer-Verlag).
We will also publish additional proceedings in a USB memory with a later
deadline.
*Tracks*
- DS track. Data science is the science of data. Its goal is to explain
processes and objects through the available data. The explanation is expected
to be objective and suitable to make predictions. The ultimate goal of the
explanations is to make informed decisions based on the knowledge extracted
from the data. Original contributions on methods, models, and tools for data
science are sought.
- DP Track. Data privacy track. Privacy-preserving data mining, privacy
enhancing technologies, and statistical disclosure control provide tools to
avoid disclosure, and/or have a good balance between disclosure risk and data
utility and security. Original contributions on aspects related to data privacy
are sought.
- AGOP Track. Aggregation functions. Functions to aggregate data appear in
several contexts. They are used for decision making and information fusion.
Data science and artificial intelligence systems need these functions to
summarize information, improve data quality and help in decision processes.
Original contributions on aggregation functions and their applications are
sought.
- DM Track. Human decision making. Decision making is a pervasive problem in
intelligent systems, and decisions are to be made in scenarios where
uncertainty is common. Most mathematical models for decision making under risk
and uncertainty provide optimal decisions under certain constraints. Experience
and studies show that these rational decision making models diverge from the
typical approach human use to make decisions.
- GSN Track. Graphs and (social) networks track. Graphs are often a convenient
way to represent data. Social networks is a paradigmatic case. Algorithms and
functions to process graphs and to extract information and knowledge from them
are of high relevance in data science. Original contributions on graph analysis
are sought.
- RS Track. Recommendation and search track. Searching and recommending online
information/items to users deals with both the subjectivity related to the
user's needs and the uncertainty and vagueness that characterize the retrieval
process, in particular on the Web and on social media where huge amounts of new
contents are generated every day. For these reasons, original contributions on
search and recommendation algorithms and applications are sought
*MDAI 2020 Organization*
General chairs:
Núria Agell (ESADE, Universitat Ramon Llull)
Jordi Nin (ESADE, Universitat Ramon Llull)
Program co-chairs:
Vicenc Torra (Maynooth University, Ireland)
Yasuo Narukawa (Toho Gakuen, Japan)
AB and PC and additional information:
http://www.mdai.cat/mdai2019_______________________________________________
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