Computer Science and Media, Bauhaus-Universität Weimar
Benno Stein (PhD) is Chair of the Web-Technology and Information Systems Group at the Bauhaus-Universität Weimar. His research focuses on modelling and solving data, and knowledge-intensive information processing tasks. He has developed theories, algorithms and tools for information retrieval, data mining and knowledge processing, as well as for engineering design and simulation (patents granted). For several achievements of his research he has been awarded with scientific and commercial prizes.
Stein studied at the University of Karlsruhe (1984–89), and completed his dissertation (1995) and Habilitation (2002) in computer science at the University of Paderborn. In 2005, he was appointed as a full Professor for Web Technology and Information Systems at the Bauhaus-Universität Weimar. He has completed research stays at IBM, Germany, and the International Computer Science Institute, Berkeley. Benno Stein serves on scientific boards, on programme committees and as reviewer in various relevant conferences and journals; he is also the initiator and a co-chair of PAN, an excellence network and evaluation lab on text forensics with focus on authorship analysis, profiling and reuse detection. He is cofounder and spokesperson of the Digital Bauhaus Lab Weimar, a recently-opened interdisciplinary research centre for Computer Science, Arts and Engineering. He is also a cofounder (1996) and scientific director of the Art Systems Software Ltd, a world-leading company for simulation technology in fluidic engineering.
Information Retrieval and Data Mining for Authorship Analysis.
This paper will introduce problems and solutions from the field of digital text forensics, such as authorship identification, vandalism in wikipedia or plagiarism detection. The development of solutions for this kind of problems forms an excellent research field that combines approaches from Information Retrieval, Machine Learning and Computational Linguistics. Furthermore, the development of effective algorithms to automatically address these and related problems has become highly relevant: in the age of nearly unlimited text access, the analysis of writing styles or text reuse requires machine support; similarly, the success of important social software projects such as the online encyclopedia wikipedia lies in its openness – which, however, makes them vulnerable to destructive activities.