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Display Omitted New distance measure between sets where set items are arranged in concept hierarchy.Natural extension of Jaccard distance to include a concept hierarchy.Improved clustering results compared with traditional approaches. ObjectiveWe introduce a new distance measure that is better suited than traditional methods at detecting similarities in patient records by referring to a concept hierarchy. Materials and methodsThe new distance measure improves on distance measures for categorical values by taking the path distance between concepts in a hierarchy into account. We evaluate and compare the new measure on a data set of 836 patients. ResultsThe new measure shows marked improvements over the standard measures, both qualitatively and quantitatively. Using the new measure for clustering patient data reveals structure that is otherwise not visible. Statistical comparisons of distances within patient groups with similar diagnoses shows that the new measure is significantly better at detecting these similarities than the standard measures. ConclusionThe new distance measure is an improvement over the current standard whenever a hierarchical arrangement of categorical values is available.

Technostress has become an important topic in the scientific literature, particularly in Information Systems (IS) research. Heart rate variability (HRV) has been proposed as a measure of (techno)stress and is widely used in scientific investigations. The objective of the pilot study reported in this paper is to showcase how the preprocessing/cleaning of captured data can influence the results and their interpretation, when compared to self-report data. The evidence reported in this paper supports the notion that NeuroIS scholars have to deliberately make methodological decisions such as those related to preprocessing of physiological data. It is therefore crucial that methodological details are presented in NeuroIS papers in order to create a better understanding of the study results and their implications.

In diesem Kapitel werden wir uns mit der Sprache der Mathematik beschaftigen. Dies wird uns erlauben, normalsprachliche Ausdrucke in prazise mathematische Aussagen umzuwandeln und aus diesen Aussagen Schlusse zu ziehen. Dazu werden wir sowohl die Struktur (Syntax) und die Bedeutung (Semantik) von Aussagen betrachten.

In diesem Kapitel betrachten wir Mengen als Grundbausteine mathematischer Objekte. Dabei verzichten wir auf eine genaue Definition des Begriffs Menge; die bekannte sprachliche Beschreibung stammt von Georg Cantor (1845–1918), dem Begrunder der Mengenlehre.