Künstliche Intelligenz & Blockchain: „Buzzword-Hochzeit“ oder Zukunftsmodell?
Wagener, Andreas (2018)
dpr – Digital Publishing Report, Nr. 1/2018, Trends 2018, S. 11.
Open Access
Technik und Recht verbinden - handhabbare Lösungen für den Mittelstand schaffen
Weber, Beatrix (2018)
Begleitforschung Smart Data: Big Data, Smart Data, Next?, S. 88-91.
Datenschutz 4.0
Weber, Beatrix (2018)
Digitalisierung - Segen oder Fluch?, S. 101-123.
Digitalisierung – Auswirkungen auf die Wohlfahrtspflege
Wolff, Dietmar (2018)
Der Paritätische Sachsen-Anhalt, Blickpunkte 01/2018, S. 36-37.
Digitalisierung: Segen oder Fluch? Wie die Digitalisierung unsere Lebens- und Arbeitswelt verändert
Wolff, Dietmar; Göbel, Richard (2018)
Was kann die Sozialbranche aus der Wirtschaft lernen – was besser nicht?
Wolff, Dietmar (2018)
Digitaler Wandel in der Sozialwirtschaft - Grundlagen-Strategien-Praxis, S. 45-56.
Entbürokratisierung – Digitale Rechnungen auf dem Vormarsch
Wolff, Dietmar (2018)
SOZIALwirtschaft 1/2018.
Providing user guidance in special purpose machines by machine-learning algorithms
Plenk, Valentin; Lang, Sascha; Wogenstein, Florian (2017)
International Journal On Advances in Software 10 (3 und 4), 167-179.
Open Access
This paper proposes to make complex production machines more user-friendly. Improved machines help the operator in case of an error message or a process event by displaying recommendations, such as “at the last 10 occurrences of this event the operators performed the following keystrokes”. The messages are generated from statistical data on former user- interaction and previous process-events. The data represents the knowledge of all the machine operators. The data is gathered by logging user-interaction and process-events during regular operation of the production machine. This approach allows to store the operators’ expert knowledge in the production machine without human intervention.
Influencer-Marketing für die Nische
Wagener, Andreas (2017)
Marconomy, 12.12.17, https://www.marconomy.de/influencer-marketing-fuer-die-nische-a-670604/, 2017 2017.
Die Akzeptanz von Smart Metern als Voraussetzung für "Energie 4.0".
Wagener, Andreas (2017)
Industry of Things, 11.12.17, https://www.industry-of-things.de/die-akzeptanz-von-smart-metern-als-voraussetzung-fuer-energie-40-a-666713/, 2017 2017.
Blockchain: Der Uber-Killer
Mit Carsten Kloth (2017): In: bizzenergy. Dezember 2017/Januar 2018, S. 50 – 55 (S. 55), 2017.
Bitcoin. Interview mit Mit: Gerhard Prockscha (2017): In: Radio Extra, 01.12.17
Wagener, Andreas (2017)
Bitcoin. Interview mit Mit: Gerhard Prockscha (2017): In: Radio Extra, 01.12.17.
Künstliche Intelligenz und Industrie 4.0: Wie Daten und Algorithmen neue Geschäftsmodelle ermöglichen
Wagener, Andreas (2017)
BARC Congress für Business Intelligence und Datenmanagement 2017, 21.11.2017, Würzburg.
Künstliche Intelligenz – wie Daten und Algorithmen unsere Welt bestimmen.
Wagener, Andreas (2017)
Digital Know-How Sessions der Commerzbank AG Frankfurt, 14.11.2017, Frankfurt a. M. .
Wie Künstliche Intelligenz Wirtschaft und Gesellschaft verändern wird.
Wagener, Andreas (2017)
Bietigheim-Bissinger Akademietage, 08.11.2017, Bietigheim-Bissingen.
Künstliche Intelligenz und Datenökonomie in der Arbeitswelt von morgen.
Wagener, Andreas (2017)
Deutsche HR-Summit der F.A.Z.-Verlagsgruppe, 27.10.2017, Frankfurt a. M. .
Blockchain und die Industrie 4.0 – Das Ende der Plattformökonomie? Wie die Technologie hinter Bitcoin Wirtschaft und Gesellschaft verändern könnte.
Wagener, Andreas (2017)
Im Rahmen der (hochschulöffentlichen) Ringvorlesung „Digitalisierung, Industrie 4.0 & das Internet der Dinge“ an der Hochschule Hof, 18.10.2017, Hof.
Scoring of machine-learning algorithms for providing user guidance in special purpose machines
Plenk, Valentin; Lang, Sascha; Wogenstein, Florian (2017)
Proceedings of CENTRIC 2017: The Tenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services, Athen.
Open Access
We propose a system to make complex production machines more user-friendly by giving the operator recommendations, such as "in the last 10 occurrences of this event the operators performed the following keystrokes". We describe algorithms to generate the recommendations based on data on former user-interaction and process values and to store them in a knowledge base. We also propose algorithms to retrieve recommendations suited to the current process state. We evaluate their performance on simulated data and data gathered from real production machines.
Tweaking the Facebook Newsfeed Algorithm
Wagener, Andreas (2017)
Guest Lecture at University of Iceland, School of Social Sciences, (Englisch), 18.09.2017, Reykjavik/Island.
Revisiting Hypertext Infrastructure
Atzenbeck, Claus; Schedel, Thomas; Tzagarakis, Manolis; Roßner, Daniel; Mages, Lucas (2017)
Atzenbeck, Claus; Schedel, Thomas; Tzagarakis, Manolis; Roßner, Daniel...
Proceedings of the 28 th ACM Conference on Hypertext and Social Media (HT'17), 35–44.
DOI: 10.1145/3078714.3078718
Open Access Peer Reviewed
Specialized systems aiming at offering hypertext functionality in users' computing have been discussed since the early days of hypertext. However, with the claim to also support other structure domains than node-link structures, hypertext systems had to overcome some challenges. Researchers came up with component-based approaches and low level structure services.
Due to the raising omnipresence of the Web, research on traditional hypertext systems has been fading out over the past decade. This paper focuses again on hypertext infrastructures and goes beyond ongoing Web discussions. Based on lessons learned from well thought through previous work, we present a novel design for multi-structure supporting, general purpose hypertext systems that can be used in a series of application domains. The system provides intelligence analysis which is needed for sophisticated user support. We argue that this lets us use the hypertext system also as a visual analytics tool. Furthermore, for demonstration purposes we describe the use of the system in combination with a Web-based software engineering platform, which is part of the ongoing project ODIN.
Institut für Informationssysteme (iisys)
Hochschule für Angewandte Wissenschaften Hof
Alfons-Goppel-Platz 1
95028 Hof
T +49 9281 409 6112
sekretariat[at]iisys.de
Grit Götz
T +49 9281 409-6112
grit.goetz[at]hof-university.de