Data linkage aims to link data from different sources in a meaningful way. This is difficult to achieve in real-world applications since the semantics of data are often ambiguous or implicitly encoded into the data level. Capturing human knowledge acquired from different sources in a reusable and collaborative way will enable us to improve quality and efficiency of data linkage over time.
This project aims to investigate logical reasoning techniques that can efficiently leverage human knowledge for improving the quality of data linkage.
Having general knowledge about databases, machine learning and logics is important.