For bachelor students we offer German lectures on database systems in addition with paper- or project-oriented seminars. Within a one-year bachelor project students finalize their studies in cooperation with external partners. For master students we offer courses on information integration, data profiling, search engines and information retrieval enhanced by specialized seminars, master projects and advised master theses.
The Web Science group focuses on various topics related to the Web, such as Information Retrieval, Natural Language Processing, Data Mining, Knowledge Discovery, Social Network Analysis, Entity Linking, and Recommender Systems. The group is particularly interested in Text Mining to deal with the vast amount of unstructured and semi-structured information available on the Web.
Most of our research is conducted in the context of larger research projects, in collaboration across students, across groups, and across universities. We strive to make available most of our data sets and source code.
We publish our research mostly at DB and IR-related journals and conferences. Many of our publications are available as downloads. If you cannot find one, please contact one of the authors.
Our group includes PostDocs, PhD students, and student assistants, and is headed by Prof. Felix Naumann. If you are interested in joining our team, please contact Felix Naumann.
Improving Company Recognition from Unstructured Text by using Dictionaries.Loster, Michael; Zuo, Zhe; Naumann, Felix; Maspfuhl, Oliver; Thomas, Dirk (2017).
Comparing Features for Ranking Relationships Between Financial Entities Based on Text.Repke, Tim; Loster, Michael; Krestel, Ralf in DSMM'17 (2017). 12:1--12:2.
Combination of Rule-based and Textual Similarity Approaches to Match Financial Entities.Samiei, Ahmad; Koumarelas, Ioannis; Loster, Michael; Naumann, Felix in DSMM'16 (2016).