Johannes Kepler University of Linz

About: Johannes Kepler University of Linz is a education organization based out in Linz, Oberösterreich, Austria. It is known for research contribution in the topics: Computer science & Thin film. The organization has 6605 authors who have published 19243 publications receiving 385667 citations.

Analyzing Internet Forums

Abstract: Within Internet forums, members of certain (online) communities discuss matters of concern to the respective groups, with comparatively few social restraints. For radical, extremist, and other ideologically “sensitive” groups and organizations in particular, Internet forums are a very efficient and widely used tool to connect members, inform others about the group’s agenda, and attract new members. Whereas members of such groups may be reluctant to express their opinions in interviews or surveys, we argue that Internet forums can yield an abundance of useful “natural” discursive data for social scientific research. Based on two exemplary studies, we present a practical guide for the analysis of such data, including data-sampling strategies, the refinement of the data for computer-assisted qualitative and quantitative analysis, and strategies for in-depth analysis. The first study is an in-depth analysis of discourses within a German neo-Nazi discussion board. In the second, nine online forums for young Ge...

Generalized smart evolving fuzzy systems

Abstract: In this paper, we propose a new methodology for learning evolving fuzzy systems (EFS) from data streams in terms of on-line regression/system identification problems. It comes with enhanced dynamic complexity reduction steps, acting on model components and on the input structure and by employing generalized fuzzy rules in arbitrarily rotated position. It is thus termed as Gen-Smart-EFS (GS-EFS), short for generalized smart evolving fuzzy systems. Equipped with a new projection concept for high-dimensional kernels onto one-dimensional fuzzy sets, our approach is able to provide equivalent conventional TS fuzzy systems with axis-parallel rules, thus maintaining interpretability when inferring new query samples. The on-line complexity reduction on rule level integrates a new merging concept based on a combined adjacency–homogeneity relation between two clusters (rules). On input structure level, complexity reduction is motivated by a combined statistical-geometric concept and acts in a smooth and soft manner by incrementally adapting feature weights: features may get smoothly out-weighted over time (\(\rightarrow\)soft on-line dimension reduction) but also may become reactivated at a later stage. Out-weighted features will contribute little to the rule evolution criterion, which prevents the generation of unnecessary rules and reduces over-fitting due to curse of dimensionality. The criterion relies on a newly developed re-scaled Mahalanobis distance measure for assuring monotonicity between feature weights and distance values. Gen-Smart-EFS will be evaluated based on high-dimensional real-world data (streaming) sets and compared with other well-known (evolving) fuzzy systems approaches. The results show improved accuracy with lower rule base complexity as well as smaller rule length when using Gen-Smart-EFS.

Impact of school inspections on improvement of schools-describing assumptions on causal mechanisms in six European countries

Abstract: School inspection is used by most European education systems as a major instrument for controlling and promoting the quality of schools. Surprisingly, there is little research knowledge about how school inspections drive the improvement of schools and which types of approaches are most effective and cause the least unintended consequences. The study presented in this paper uses interviews with inspection officials and a document analysis to reconstruct the “program theories” (i.e. the assumptions on causal mechanisms, linking school inspections to their intended outcomes of improved teaching and learning) of Inspectorates of Education in six European countries. The results section of the paper starts with a summary of the commonalities and differences of these six national inspection models with respect to standards and thresholds used, to types of feedback and reporting, and to the sanctions, rewards and interventions applied to motivate schools to improve. Next, the intermediate processes through which these inspection models are expected to promote good education (e.g. through actions of stakeholders) are explained. In the concluding section, these assumptions are critically discussed in the light of research knowledge.