Techniques for the automated analysis of large text contributions and the identification of topics, argument structures, sentiments and emotions.
- How can text contents be automatically clustered and classified?
- How can expressive sentiments be distinguished from opinions and arguments?
- How can the design of input formats support automated analysis?
- How can patient discussions on diabetic online forums be automatically summarized and interpreted?
Contact
Prof. Dr. Stefan Conrad (vice speaker)
Board, Computer Science, DIID-Team
Prof. Dr. Stefan Conrad has held the Chair of Databases and Information Systems at the Institute of Computer Science since 2002. He has been a member of the Senate of HHU-Düsseldorf since 2015. In his research, he works on issues related to the analysis of large data sets, especially in image retrieval, time series analysis, clustering, and text mining.
He has been cooperating with practice partners for many years, especially in several BMWi-funded ZIM projects on opinion mining, extraction of product features important for users, and automated text summarization.
At DIID, he is interested in researching techniques for automated topic detection and content analysis of text contributions as well as the identification of argument structures, subjective evaluations, and emotions.
Prof. Dr. Stefan Conrad was re-elected as Deputy Spokesperson of the DIID by the DIID General Assembly in December 2023.