The abundance of available data that is retrieved from or is related to the areas of Humanities challenges the research community in processing and analyzing it. The aim is two-fold: on the one hand, to extract knowledge that will help understand human behavior, communication, creativity, way of thinking, reasoning, learning, decision making, socializing; on the other hand, to exploit the extracted knowledge by incorporating it into intelligent systems that will support humans in their everyday activities. The nature of humanistic data can be multimodal, dynamic, time and space-dependent, and highly complicated. Translating humanistic information, e.g. behavior, state of mind, artistic creation and linguistic utterance, into numerical or categorical low-level data is a significant challenge on its own. New mining techniques, appropriate to deal with this type of data, need to be proposed and existing ones adapted to its special characteristics. The proposed special issue aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing mining and knowledge discovery techniques (like decision rules, decision trees, association rules, clustering, filtering, learning, classifier systems, neural networks, support vector machines, preprocessing, post processing, feature selection, visualization techniques) to data derived from Humanistic Sciences, e.g. linguistic, historical, behavioral, psychological, artistic, musical, educational, social etc.

Elsevier International Journal of Computers and Electrical Engineering. Special section on “New Trends in Humanistic Informatics: Implementations and Applications” / Spyros, Sioutas; Velegrakis, Ioannis; Valia, Kordoni. - ELETTRONICO. - (2018).

Elsevier International Journal of Computers and Electrical Engineering. Special section on “New Trends in Humanistic Informatics: Implementations and Applications”

Velegrakis, Ioannis;
2018-01-01

Abstract

The abundance of available data that is retrieved from or is related to the areas of Humanities challenges the research community in processing and analyzing it. The aim is two-fold: on the one hand, to extract knowledge that will help understand human behavior, communication, creativity, way of thinking, reasoning, learning, decision making, socializing; on the other hand, to exploit the extracted knowledge by incorporating it into intelligent systems that will support humans in their everyday activities. The nature of humanistic data can be multimodal, dynamic, time and space-dependent, and highly complicated. Translating humanistic information, e.g. behavior, state of mind, artistic creation and linguistic utterance, into numerical or categorical low-level data is a significant challenge on its own. New mining techniques, appropriate to deal with this type of data, need to be proposed and existing ones adapted to its special characteristics. The proposed special issue aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing mining and knowledge discovery techniques (like decision rules, decision trees, association rules, clustering, filtering, learning, classifier systems, neural networks, support vector machines, preprocessing, post processing, feature selection, visualization techniques) to data derived from Humanistic Sciences, e.g. linguistic, historical, behavioral, psychological, artistic, musical, educational, social etc.
2018
Amsterdam
Elsevier
Elsevier International Journal of Computers and Electrical Engineering. Special section on “New Trends in Humanistic Informatics: Implementations and Applications” / Spyros, Sioutas; Velegrakis, Ioannis; Valia, Kordoni. - ELETTRONICO. - (2018).
Spyros, Sioutas; Velegrakis, Ioannis; Valia, Kordoni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/164607
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