André Melo has defended his PhD thesis on “Automatic Refinement of Large-Scale Cross-Domain Knowledge Graphs”, supervised by Prof. Heiko Paulheim.
In his thesis, André has developed different methods to improve large-scale, cross-domain knowledge graphs along various dimensions. His contributions include, among others, a benchmarking suite for knowledge graph completion and correction, an effective method for type prediction using hierarchical classification, and a machine-learning based method for detection wrong relation assertions. Moreover, he has proposed methods for error correction in knowledge graph, and for distilling high-level tests from individual errors identified.
As of September, André will start a new job as a knowledge engineer for Babylon Health in London. We wish him all the best!