Special Issue "Humanistic Data Processing"
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (6 December 2016)
Dr. Christos Makris
Dr. Phivos Mylonas
Department of Informatics, Ionian University, Kerkira, Greece
Website | E-Mail
Interests: knowledge-assisted multimedia analysis; multimedia information retrieval; multimedia personalization; user adaptation; user modeling; user profiling; visual context representation and analysis; human–computer interactions
Data processing and analysis could be described as being one of the most important, yet challenging tasks of our era. The abundant amount of available information retrieved from, or related to the areas of Humanistic Sciences poses significant challenges to the research community. The ultimate goal is two-fold: on the one hand, to extract knowledge that will aid human behavior understanding, increasing human creativity, learning, decision making, socializing and even biological processing; on the other hand, to extract and exploit the underlying semantic knowledge by incorporating it into computationally intelligent systems.
The nature of humanistic data can be multimodal, semantically heterogeneous, dynamic, time and space-dependent, and highly complicated. Translating humanistic information, e.g., behavior, state of mind, artistic creation, linguistic utterance, learning and genomic information into numerical or categorical low-level data is a significant challenge on its own. New algorithms, appropriate for dealing with this type of data, need to be proposed and existing ones adapted to the individual special characteristics.
This Special Issue aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing data matching, fusion and mining and knowledge discovery and management techniques (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, visualization techniques) to data derived from all areas of Humanistic Sciences, e.g., linguistic, historical, behavioral, psychological, artistic, musical, educational, social, etc. The Issue is devoted to the exploitation of the many facets of the above fields and will explore the current related state-of-the-art. Its topics of interest cover the scope of the MHDW 2016 workshop (https://conferences.cwa.gr/mhdw2016/). Extended versions of papers presented at MHDW 2016 are sought, but this Call for Papers is fully open to all who want to contribute by submitting a relevant research manuscript.
Dr. Katia Lida Kermanidis
Dr. Christos Makris
Dr. Phivos Mylonas
Dr. Spyros Sioutas
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- humanistic sciences
- data matching and fusion,
- data mining,
- knowledge discovery and management,
- artificial intelligence,
- information retrieval, context, social data analytics