About us ...

E-Business and E-Commerce include, besides other influencing domains, rapid changes to economic and social processes. For this reason, the research area pursues taking an encompassing view at such processes reaching from analyzing enterprises and their respective processes to evaluating the entire market, as well as is active in creating ideas and solutions for meeting the demands of the respective stakeholders.
   Overall, the electronic commerce research area performs research and creates solutions in the Business-2-Business (B2B) and Business-2-Consumer (B2C) domains. In the B2B domain, the group focuses on (i) business (process) modeling and definition and consequently the specification and implementation of e-business systems while considering and contributing to semantic web research and service-oriented architectures, (ii) ontology engineering and information integration, (iii) "Web Science" focusing on network analysis and content as well as text mining. In the B2C domain, the group performs research targeting (i) visual interaction paradigms as well as (ii) mobile applications. Thereby, our group focuses especially on the development and application of our research in the area of e-tourism and its mobile applications.
   Data Intelligence refers to the intelligent interaction with data in a rich, semantically meaningful ways, where data are used to learn and to obtain knowledge (in a pragmatic sense). In this context one may distinguish between a data and an interaction layer. At the data layer, methods come from online analytics, data mining, and machine learning. At the intelligent interaction layer, the focus is on recommender systems and information retrieval. Beyond the basic research on the foundations of these approaches, emphasis is also put on the adaptation of these approaches to specific domains, as well as evaluation methodologies (both empirical and user-centred). Domains in which we have done research include: Intellectual Property, technical & scientific publications, health & medicine, and enterprise social networks.
   High Performance Computing (HPC) Systems possess high level of computing performance compared to a general-purpose computer. Nowadays virtualized HPC systems are used to address balancing issue between overall system performance and energy efficiency. We conduct research in the area of energy efficient HPC system by developing speculative methodologies and techniques to allocate resources in an energy efficient way, but at the same time meet requirements of the end users, like the certain latency of the applications. We strive to develop generic methods and methodologies but we let our research be inspired by a set of real world applications from different domains like life sciences (e.g., DNA sequencing) or social media applications.