Advances in Data Analysis and Classification - Special Issue on New Methodologies in Clustering and Classification for Complex and/or Big Data

The journal Advances in Data Analysis and Classification will publish a Special Issue on New methodologies in Clustering and Classification for Complex and/or Big Data, associated to the conference

IFCS 2022: Classification and Data Science in the Digital Age.

This Special Issue aims at gathering excellent papers in different areas related to modern statistical approaches for the analysis of complex and/or big data. Topics of particular interest may include, but are not limited to:

Methodological innovations in the statistical model-based approaches for classification, clustering, dimension reduction and analysis of complex and/or big data.Methodological innovations in the fields of statistical learning devoted to classification, clustering, dimension reduction and analysis of complex and/or big data.Robust modeling for data classification, clustering, dimension reduction and analysis of complex and/or big data.Developments and applications of these methods in modern and relevant domains such as bioinformatics, biostatistics, epidemiology, biology, business, finance, marketing, image analysis, pattern recognition, process control, correlated and functional data, symbolic data, social networks, policy making, etc.Development of specific computational and graphical tools.

All manuscripts submitted to this Special Issue will undergo the classical double-blind reviewing process of the journal. Manuscripts should be submitted using the “Submit manuscript” button on the ADAC website http://www.springer.com/journal/11634 (this opens in a new tab), leading to the electronic submission system of the journal.

Important dates:

Submission of full papers for the Special Issue: November 30th, 2022 (earlier submission is encouraged).Notification to authors: April 1st, 2023 (tentative).Final papers: June 30, 2023 (tentative).

Guest Editors:

Prof. Paula Brito

Faculdade de Economia

Universidade do Porto

Rua Dr. Roberto Frias – 4200-464 Porto, Portugal

mpbrito@fep.up.pt (this opens in a new tab)

Prof. Andrea Cerioli (Lead Guest Editor)

Dipartimento di Scienze Economiche e Aziendali

Università di Parma

Via Kennedy 6 – 43125 Parma, Italy

andrea.cerioli@unipr.it (this opens in a new tab)

Prof. Luis Angel García Escudero