Knowledge graphs (KGs) are becoming the foremost driving force to enable the Artificial Intelligence (AI). Like human brains, knowledge graphs will become the brains for machines that can connect dots, perform cognitive inference, and most importantly, derive insights from the vast amount of heterogeneous data. The cutting-edge machine learning and deep learning algorithms can empower machines to detect hidden patterns and build strong memories beyond human imagination, but if the data is siloed (or disconnected), no matter how big it is, it is powerless. Knowledge graph is the necessary step to integrate disparate datasets and build machine processible knowledge to enable intelligent machine learning and deep learning.Graph data model will replace the relational data model to become the prominent data model to realize the intelligence of AI. Because the relationships of data are critical to understand the complexity about organizations, people, biological entities, and financial transactions. Gartner predicted that knowledge graph application and graph mining will grow 100% annually through 2022 to enable more complex and adaptive data science. In regard to 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.
Due to COVID-19 pandemic, we will work closely with KDD conference organizers to investigate feasible options to make this workshop successful.
The workshop will be open for the whole conference. Each paper will be evaluated by three reviewers from the aspects of novelty, significance, technique sound, experiments, and presentations. The reviewers will be program committee members or researchers recommended by the members.
Building KGs using NLP
Visual searching and intelligent browsing KGs
Industrial applications of KGs: banking, financing, retail, healthcare, medicine, pharma, etc.
KGs powered machine learning and deep learning
KGs in computer vision, medical imaging
KGs for AI ethics and misinformation
Machine learning, including deep learning, algorithms on KGs
Inferencing on KGs
Intelligent services using KGs: chatbot, virtual assistant
KGs for explainable AI
Semantic web and KGs