S
Stefan Arbanowski
Researcher at Fokus
Publications - 84
Citations - 787
Stefan Arbanowski is an academic researcher from Fokus. The author has contributed to research in topics: IPTV & Service (systems architecture). The author has an hindex of 14, co-authored 79 publications receiving 753 citations. Previous affiliations of Stefan Arbanowski include Fraunhofer Institute for Open Communication Systems & Free University of Berlin.
Papers
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Journal ArticleDOI
I-centric communications: personalization, ambient awareness, and adaptability for future mobile services
Stefan Arbanowski,Pieter Ballon,Klaus David,Olaf Droegehorn,Henk Eertink,Wolfgang Kellerer,H. van Kranenburg,K. Raatikainen,Radu Popescu-Zeletin +8 more
TL;DR: Major service capabilities such as personalization, ambient awareness, and adaptability are described along with a reference model focusing in I-centric communication, which is a service infrastructure framework for the future wireless world.
Proceedings ArticleDOI
pREST: a REST-based protocol for pervasive systems
TL;DR: This work presents an access protocol to bring the Web's simplicity and holistic view on data and services to pervasive systems, based on the representational state transfer architectural style and emphasizes abstraction of data and Services as resources.
Proceedings ArticleDOI
Service personalization for unified messaging systems
TL;DR: This paper investigates how different services could be personalized in a unified way by unified messaging systems, and a generic approach for service personalization is given.
Context Acquisition, Representation and Employment in Mobile Service Platforms
Anna V. Zhdanova,Josip Zoric,Marco Marengo,Herma van Kranenburg,Niels Snoeck,Michael Sutterer,Christian Räck,Olaf Droegehorn,Stefan Arbanowski +8 more
TL;DR: This work presents context acquisition, context representation, context enabling and use in mobile service platforms, and outlines the main ontological enablers of the shared communication sphere, and illustrates their added value with a scenario.
Proceedings ArticleDOI
Context-aware, ontology-based recommendations
TL;DR: A system that delivers context-aware recommendations, which are based on provided feedback, context data, and an ontology-based content categorization scheme are proposed.