Knowledge Graph Embedding

Talk by Michael Cochez

Location: APB 3027
Start: 7. February 2019 at 1:00 pm
End: 7. February 2019 at 2:30 pm
Research group: Computational Logic
Event series: KBS Seminar
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Abstract: Recently graph embeddings have been taken up by the community as a tool to solve various tasks in machine learning and the general AI community. In this talk I will give a gentle introduction to the topic and also give some pointers to currently ongoing research. We start from looking at why graph embeddings are needed in the first place and how they could be used. We will then focus on graphs containing a large variety of information, typically called knowledge graphs, often represented in RDF. These graphs are hard to embed compared to e.g., uniform simple networks) because they contain multiple edge and vertex types, relation directionality, literals, etc. What we will cover are a few basic techniques on how these embeddings can be computed. We plan to look into at least one example of translational based methods, one from matrix decomposition, and methods based on co-occurrence and statistical information. Finally we will discuss about a couple of open problems and some of the topics currently worked on.

Short biography: Michael Cochez is a postdoctoral researcher at the Fraunhofer Institute for Applied Information Technology FIT in Germany. In this position Michael is working on transferring research results from the academic world to the industry. Besides the industry exposure, he conducts research in areas related to data analysis and knowledge representation, like knowledge graph embedding, scalable clustering, frequent itemset mining, stream sampling, prototype-based ontologies, ontology matching, and knowledge evolution. This research is currently mainly conducted at the RWTH Aachen university, Germany. Before joining Fraunhofer, he obtained his Ph.D. degree from the University of Jyväskyä, Finland under the supervision of Vagan Terziyan and Ferrante Neri (De Montfort University - Leicester). He obtained his master degree from the same university and his bachelor degree from the University of Antwerp, Belgium. Michael Cochez is currently on a partial leave from a postdoc at the University of Jyväskylä and is also a scientific advisor for WE-OPT-IT Oy (former MyOpt Oy) in Finland.