Panel Discussion

Knowledge Graph: Past, Present and Future

Knowledge graph (KG) is becoming the foremost driving force to enable the cognitive AI. Like human brains, knowledge graphs will become the brains for machines that can connect dots, perform cognitive inference, and the most important, to find insights from the vast amount of data. The cutting-edge machine learning and deep learning algorithms can empower machines to detect hidden patterns and build strong memories beyond human imagination. Gartner predicted that knowledge graph application and graph mining will grow at 100% annually through 2022 to enable more complex and adaptive data science. Given the black box nature of AI algorithms, explainable AI becomes indispensable for applications which demand transparent decision makings. Knowledge graph can play an essential role to decipher the hidden connections and complex contexts into traceable paths. Therefore, knowledge graphs have been widely applied in drug discovery, fraud detection, healthcare, financial intelligence, business intelligence, chatbot, virtual assistant, and robots. This panel will look at the wide spectrum of knowledge graph, from it was, to it is, and envisions it will be.

– Francois Scharffe, Columbia University, USA

– Paul Groth, University of Amsterdam, the Netherlands

– Axel Polleres, WU Vienna, Austria

– Ying Ding, University of Texas at Austin, USA (Organiser)

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