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hi my name is Ching Wong Ill be presenting our work on orthogonal relation transforms with graphed context modeling for knowledge graph embedding this is joint work with my colleagues in Kanto Sheldon Pawan at JDI research Ill start with introduction on knowledge graph embedding and review some related works then Ill present our new proposed orthogonal transform embedding OTE and how to add graph contacts to OTE then I will present our experimental setup and results on common benchmark data sets and concluded hog with a summary knowledge graph is a multi relational graph with node represent entities and edge represent relations between entities for example here we see da Vinci painted Mona Nisa this fact is represented as a head relation tail triple these structured knowledge in knowledge graph are helpful for various applications such as search question answering and other applications existing law graphs are far from completion and they are missing links and entities so the task
