Research Areas ǀ Knowledge Technologies for Society

This part of our work is concerning the use of knowledge technologies for solving practically relevant problems from many different areas, ranging from agriculture and industry, through medicine and healthcare, to media, education, industry, and space sector.

In the area of agriculture and environment we are using data mining and decision modeling methods to develop predictive and decision models to support sustainable agricultural development. We are developing decision support systems (DSS): Pathfinder (for assessing and managing the sustainability of agri-food chains), ResourceAmplifier (for a selection of management measures that improve water and nutrient resource efficiency for tomato production) …

In the area of health and well-being a computerized system to help patients and doctors in the management of congestive heart failure is developed. We are also developing a virtual assistant-coach that supports the aging population living at home. Our work focused on development of modeling and reasoning components of the coaching system, we prepared the modules for sleep quality, cooking activity, mobility and social activity. All modules were tested in real-life installations within the pilot study. In order to increase the effectiveness of coaching we have also developed a novel method for preference learning based on user’s feedback as reported for different coaching messages that were received by the users. We are also developing several disruptive decision support models included in two web platforms: for human resources management for customs office and for public employment services. The development of decision models continued for private employment services as well.

In the area of knowledge technologies for education, our activities broadened the scope of target open education applications to also cover management processes, such as identifying knowledge gaps, quality assessment and shaping strategic policies. We aimed at enhancing cooperative creation of Open Educational Resources (OER) for implementation of Sustainable Development Goals (SDGs).

We are also applying knowledge technologies to problems from industry, with a focus on the space sector: use of machine learning for Earth observation and space operations. We are studying the outliers appearing in the telemetry data and the effect of data frugality and different operations contexts on the predictive performance of the learned models. Finally, we have presented a toolbox for interpretable analysis of spacecraft telemetry data.

Contact: Marko Debeljak, Bernard Ženko, Dragi Kocev

Projects in the field of Knowledge Technologies for Society: