The mission of the Knowledge Discovery group is to extract the maximum value out of data. To that end, we follow a data-driven approach, which is domain-agnostic in its application. Our research is related to the scientific fields of machine learning, natural language processing and information retrieval. Methods from these fields form the algorithmic base of data science, artificial intelligence and interactive applications.
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Effective Use of BERT in Graph Embeddings for Sparse Knowledge Graph Completion ACM SAC 2022 Track on Knowledge Graphs
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Impact of Training Instance Selection on Domain-Specific Entity Extraction using BERT NAACL 2022 student research workshop
