DSGVO an Schulen: Datenschutz aus Sicht der Lehrkräfte

Fehlende Information über die europäische Datenschutzgrundverordnung (DSGVO) stiftet zurzeit auch im Bildungsbereich unnötig Verwirrung. Was ist erlaubt und was nicht? Dieser Artikel nimmt sich des Themas abseits von Hysterie und Fehlinformation an. Datenschutz ist ein Grundrecht und für eine lebendige Demokratie unerlässlich. Deshalb sollten wir ihn im Unterricht nicht ausklammern. Dieser Text gibt Infos und Tipps für Datenschutzbereiche, die für LehrerInnen in ihrer Unterrichtsgestaltung und dem Schulbetrieb relevant sind

Service Re-Selection for Disruptive Events in Mobile Environments: A Heuristic Technique for Decision Support at Runtime

Modern service-based processes in mobile environments are highly complex due to the necessary spatial–temporal coordination between multiple participating users and the consideration of context information. Due to the dynamic nature of mobile environments, disruptive events occur at runtime, which require a re-selection of the planned service compositions respecting multiple users and context-awareness. Thereby, when re-selecting services the features performance, solution quality, solution robustness and alternative solutions are essential and contribute to the efficacy of service systems. This paper presents an optimization-based heuristic technique based on a stateful representation that uses a region-based approach to re-select services considering multiple users, context information and in particular disruptive events at runtime. The evaluation results, which are based on a real-world scenario from the tourism domain, show that the proposed heuristic is superior compared to competing artifacts

Something’s Missing? A Procedure for Extending Item Content Data Sets in the Context of Recommender Systems

The rapid development of e-commerce has led to a swiftly increasing number of competing providers in electronic markets, which maintain their own, individual data describing the offered items. Recommender systems are popular and powerful tools relying on this data to guide users to their individually best item choice. Literature suggests that data quality of item content data has substantial influence on recommendation quality. Thereby, the dimension completeness is expected to be particularly important. Herein resides a considerable chance to improve recommendation quality by increasing completeness via extending an item content data set with an additional data set of the same domain. This paper therefore proposes a procedure for such a systematic data extension and analyzes effects of the procedure regarding items, content and users based on real-world data sets from four leading web portals. The evaluation results suggest that the proposed procedure is indeed effective in enabling improved recommendation quality

Data Quality in Recommender Systems: The Impact of Completeness of Item Content Data on Prediction Accuracy of Recommender Systems

Recommender systems strive to guide users, especially in the field of e-commerce, to their individually best choice when a large number of alternatives is available. In general, literature suggests that the quality of data which a recommender system is based on may have important impact on recommendation quality. In this paper, we focus on the data quality dimension completeness of item content data (i.e., features of items and their feature values) and investigate its impact on the prediction accuracy of recommendations. Besides the general impact of completeness, we specifically examine this impact depending on the increase in completeness per item, per user and per feature. To this end, we present a theoretical model based on the literature and derive ten hypotheses. We test these hypotheses on large real-world data sets from two leading web portals for restaurant reviews. While the results strongly support that, in general, the prediction accuracy is positively influenced by increased completeness, the results further reveal some interesting findings which are contrary to statements in existing literature