Conference Information

MDAI 2020: International Conference on Modeling Decisions for Artificial Intelligence

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Submission Date:
2020-03-31 Extended
Notification Date:
2020-05-02
Conference Date:
2020-09-02
Location:
Sant Cugat, Catalonia, Spain
Years:
17
CORE: b   QUALIS: b3   Viewed: 22597   Tracked: 1   Attend: 1

Call For Papers

MDAI 2020 (International Conference on Modeling Decisions for Artificial Intelligence) is a CORE B / QUALIS B3 conference held in Sant Cugat, Catalonia, Spain on 2020-09-02. The paper submission deadline is 2020-03-31 (extended). Acceptance notifications are sent on 2020-05-02.

DS Track. 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. 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 Publication: Proceedings will be published in the LNAI/LNCS series (Springer-Verlag), and distributed at the conference. Besides, papers, that according to the evaluation of the referees, are not suitable for the LNAI but that have some merits will be published in accompanying proceedings and scheduled in the MDAI program. Papers can be directly submitted for the accompanying proceedings.
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