Dear all,
hope you are well. Sorry for multiple postings. CFP below.
MDAI 2022 will be held in in Sant Cugat, very close to Barcelona.
vicenc
Umea University, Sweden
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CALL FOR PAPERS
19th Modeling Decisions for Artificial Intelligence
MDAI 2021, Sant Cugat, Catalonia, Spain
30 August - 2 September, 2022
http://www.mdai.cat/mdai2022
Proceedings: LNAI; CORE-B conference; Deadline: March 15th
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, (vii) recommendation
and search. 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),
cancelled due to COVID (2020).
MDAI is rated as a CORE B conference by the Computing Research and Education
Association of Australasia - CORE.
*Important Dates*
LNAI Submission deadline: March 15th, 2022
LNAI Acceptance notification: May 2nd, 2022
ISBN/Downloadable-only Submission deadline: June 15th, 2022
ISBN/Downloadable-only Acceptance notification: July, 15th, 2022
Final version of LNAI accepted papers: May 22nd, 2022
Early registration: June 9th, 2022
Conference: 30 August - 2 September, 2022
*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*
Data Science 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.
Machine learning track. Algorithms and methods building models that are fair,
transparent, explainable and that avoid unnecessary disclosure of sensitive
information.
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.
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.
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.
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.
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 2022 Organization*
General chair:
Jordi Nin (ESADE, Universitat Ramon Llull)
Program co-chairs:
Vicenc Torra (Umea University, Sweden)
Yasuo Narukawa (Tamagawa University, Japan)
Organization Chair
Núria Agell (ESADE, Universitat Ramon Llull)
Irene Unceta (ESADE, Universitat Ramon Llull)
AB, PC, local organizing committee and additional information:
http://www.mdai.cat/mdai2022_______________________________________________
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