Humanistic Data Mining: Tools and Applications

Dear Colleagues,

Digital data mining could be described as one of the most important, computationally intensive and challenging tasks of our era. As this observation applies both to the research community, which is faced with enormous challenges derived from (big-)data management as well as new emerging disciplines like, for instance, precision agriculture, and the applied world, in terms, for instance, of social data handling and related social apps, it is becoming evident that new approaches have to be followed and new tools and applications have to invented in order to efficiently handle the vast amounts of information.

The aim of the “Mining Humanistic Data Workshop”, and by association of the proposed Special Issue, is formed around two main pillars. The first pillar focuses on the primitive information and knowledge analysis, as well as the extraction of the inherited knowledge. The task here is to achieve a better understanding of human activities associated to the respective computational tasks. The second pillar aims to exploit the extracted knowledge by incorporating it into smart tools and applications; the latter will ultimately make the life of involved users easier with respect to their everyday life.

This Special Issue aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing humanistic data mining and knowledge discovery and management methodologies. Since humanistic data typically are dominated by semantic heterogeneity and are quite dynamic in nature, computer science researchers are obliged and encouraged to develop new suitable algorithms, tools and applications to efficiently tackle them, whereas existing ones need to be adapted to the individual special characteristics using traditional methodologies, such as decision rules, decision trees, association rules, ontologies and alignments, clustering, filtering, learning, classifier systems, neural networks, support vector machines, preprocessing, post processing, feature selection and visualization techniques. The Special Issue is devoted to the exploitation of the multiple facets of the above research fields and will explore the current related state-of-the-art. Its topics of interest cover the scope of the MHDW 2018 workshop (https://conferences.cwa.gr/mhdw2018/). Extended versions of papers presented at MHDW 2018 are sought, but this Call for Papers is also fully open to all who want to contribute by submitting a relevant research manuscript.

Dr. Phivos Mylonas
Dr. Katia Lida Kermanidis
Dr. Christos Makris
Dr. Spyros Sioutas
Dr. Vasileios Megalooikonomou
Guest Editors

Manuscript Submission Information

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