Teaching

The CSS Group holds courses and seminars covering contents from the following areas. Supervised bachelor's and master's theses usually are related to the main research topics of the group. Details can be found on the course page and the thesis page.

Computational argumentation deals with the computational analysis and synthesis of natural language arguments and argumentation, usually in an empirical data-driven manner. The covered tasks range from the mining of arguments from text, over the assessment of argumentation properties, to the generation of new arguments and argumentative texts.

Computational argumentation is currently most studied in the context of natural language processing, but also covers aspects of information retrieval, machine learning, classical artificial intelligence, logic and reasing, as well as visualization and human-computer interaction.

Text mining deals with the automatic or semi-automatic discovery of new, previously unknown information of high quality from large numbers of unstructured texts. The types of information to be inferred from the texts are usually specified beforehand, i.e., text mining tackles given tasks.

Text mining commonly requires to perform three steps in sequence, each of which can be associated to one field: Information retrieval, to gather input texts that are potentially relevant for the task, natural language processing, to analyze input texts in order to identify and structure relevant information, and data mining, to discover patterns in the structured information that has been inferred from the texts.

The CSS Group is also one of the groups that may hold the fundamental computer science course on modeling with formal calculi (including graphs, logic, grammars, and automata). Besides, seminars are offered from time to time on current research topics, including computational social science and computational sociolinguistics.