The increasing amount and heterogeneity of data in distributed environments, such as the Web, poses challenges with respect to searching, using and understanding data.
Our research at the intersection of semantic technologies, information retrieval and artificial intelligence aims at improving usability of heterogeneous data, information and knowledge on the Web. In particular, we develop methods and tools for retrieval, extraction and verification of entity-centric knowledge, facts or claims, for linking and semantic enrichment of large corpora, such as Web crawls or bibliographic archives) or, to automatically understand, classify and support user’s search and navigation behavior.
A specific application focus is on research information and data, in particular, for the social sciences. As part of the scientific leadership of the department “Knowledge Technologies for the Social Sciences” at “GESIS – Leibniz Institute for the Social Sciences”, our research group applies research results as part of innovative data-driven infrastructures.