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Stanford University seminar: Knowledge Graphs for Natural Language Processing

Knowledge Graph will be the key area of discussion at the masterclass How should AI explicitly represent knowledge? Organized by the Department of Computer Science, Stanford University on April 28, 2020, the course will be featuring prominent researchers and industry practitioners showcasing how latest research in Artificial Intelligence, database systems and human computer interactions are coming together in integrated intelligent systems around knowledge graphs.

José Manuel Gómez-Pérez, Expert System R&D & International Projects Director, will give a seminar session titled Knowledge Graphs for Natural Language Processing (NLP), introducing Expert System AI Knowledge Graph as an industrial NLP framework.

The seminar will be focused on how knowledge graphs can

  • contribute to train more expressive models that are able to learn the meaning of words by linking them to explicitly represented concepts in the graph;
  • streamline the models training by jointly learning word and concept representations from both the knowledge graph and a text corpus as embeddings in a common vector space
  • suggest new concepts in a knowledge graph, merging previously existing concepts, and supporting the alignment of existing knowledge graphs.