CLARIN makes digital language resources available to scholars, researchers, students and citizen-scientists from all disciplines, especially in the humanities and social sciences, through single sign-on access. CLARIN offers long-term solutions and technology services for deploying, connecting, analyzing and sustaining digital language data and tools. CLARIN supports scholars who want to engage in cutting edge data-driven research, contributing to a truly multilingual European Research Area.
Teaches basic aspects of complexity and complex systems, answering the question: What makes a system complex? Aspects that will be covered include nonlinearity, order disorder & chaos, emergence and complex adaptive systems Introduces methods, models and simulation tools to study the behaviours of complex systems and provide hands-on experience on through the use of software for building, simulating and visualizing complex networks. Participants are encouraged to bring their own data, work in groups mentored by instructors. Participants will then have the opportunity to present their own findings at the end of the week long course.
Founded in 1979, the Association for the Advancement of Artificial Intelligence (AAAI) (formerly the American Association for Artificial Intelligence) is a nonprofit scientific society devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. AAAI aims to promote research in, and responsible use of, artificial intelligence. AAAI also aims to increase public understanding of artificial intelligence, improve the teaching and training of AI practitioners, and provide guidance for research planners and funders concerning the importance and potential of current AI developments and future directions.
The vision of the MOVING project is to develop an innovative training platform that enables people from all societal sectors (companies, universities, public administration) to fundamentally improve their information literacy by training how to use, choose, reflect and evaluate data/text mining methods in connection with their daily research tasks. We believe that an extensive distribution of this type of information literacy education in the sense of a data-savvy information professional will have a decisive impact on the innovative capacity of the European society.
Imbalanced classification tasks have been studied by the research community for a long time. Numerous problems have been identified with standard approaches and new proposals have been put forward for addressing these relevant tasks. Surprisingly, the same attention has not been given to predictive tasks with a numeric target variable, i.e. As in classification standard evaluation metrics fail, and new approaches are required to bias the learning algorithms to the end-user goals.