Data guides the path of applications. Big data technologies are enabling new paths which can deal with information in a reasonable time and arrive at an approximate solution, rather than a more exact result in an unacceptably long time. This is particularly important today as we continue to work against the COVID-19 pandemic.

The conference series Modern Management based on Big Data (MMBD) has held its second edition, whereas the conference series Machine Learning and Intelligent Systems (MLIS) has held its third edition.

MMBD deals with two main branches; those of Big Data and Modern Management. The former includes: data capture and storage; search, sharing, and analytics; big data search, mining and visualization; big data technologies; data visualization; architectures for massive parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; scalable storage systems; and big data for business, government and society, among other things. The latter encompasses: modern management; management strategy; management decision making; manufacturing systems; logistic systems; facilities planning; cost analysis; engineering economy; total quality management; management information systems; human factor engineering; and human resources.

The MLIS conference is an annual conference that aims to provide a platform for knowledge exchange of the most recent scientific and technological advances in the field of machine learning and intelligent systems. It also aims to strengthen links in related fields within the scientific community.

This book, which is in two parts, contains accepted papers presented at MMBD 2021 and MLIS 2021. The MMBD conference was originally scheduled to be held from 8–11 November 2021 in Quanzhou, China and MLIS was originally scheduled to be hosted in Xiamen, China on the same dates. The most popular topics in this book concern data analysis and big data applications.

All papers have been conscientiously reviewed by programme committee members, who bore in mind the breadth and depth of the research topics that fall within the scope of MMBD and MLIS respectively. From the some 300 submissions received for MMBD and MLIS, the 78 most promising and FAIA mainstream-relevant contributions have been included in this two-part volume. These present original ideas or results of general significance supported by clear reasoning, compelling evidence and rigorous methods.

I would like to thank all the keynote and invited speakers, as well as the authors and anonymous reviewers, for their effort in making both MMBD and MLIS conferences of the highest standard. We would also like to take this opportunity to express our gratitude to all those people, especially the programme committee members and reviewers, who devoted time to assessing the papers. It is an honour to have been involved from the outset with the publication of these proceedings, which will form part of the prestigious series Frontiers in Artificial Intelligence and Applications (FAIA) from IOS Press. Our particular thanks also go to J. Breuker, N. Guarino, J.N. Kok, R. López de Mántaras, J. Liu, R. Mizoguchi, M. Musen, S.K. Pal and N. Zhong, the FAIA series editors, for supporting this conference.

Last but not least, any inconvenience caused due to the format change from face to face to virtual is sincerely regretted. Hopefully we will meet face to face at the MMBD2022 and MLIS 2022 conferences next year, the venues for which have not been decided at the time of publication.

September 2021

Antonio J. Tallón-Ballesteros

University of Huelva (Spain)

Huelva city, Spain