Dr. Craig Knoblock: Building Knowledge Graphs from Online Sources to Solve Societal Problems
We can build impactful applications from the data locked up in web sites, stored in spreadsheets, or contained in databases by turning those sources into an integrated semantic network of data, called a knowledge graph. However, exploiting the available data to build knowledge graphs is difficult due to the heterogeneity of the sources, scale in the amount of data, and noise in the data. In this talk I will present our approach to building knowledge graphs, including acquiring data from online sources, extracting information from those sources, aligning and linking the data across sources, and building and querying knowledge graphs at scale. We have applied our approach, to a variety of challenging real-world problems including combating human trafficking by analyzing web ads, identifying illegal arms sales from online marketplaces, predicting cyber-attacks using data extracted from both the open and dark web, and estimating potential threats in space by integrating the combination of structured and unstructured data on the web.
Craig Knoblock is Executive Director of the Information Sciences Institute of the University of Southern California (USC), Research Professor of both Computer Science and Spatial Sciences at USC, and Director of the Data Science Program at USC. He received his Bachelor of Science degree from Syracuse University and his Master’s and Ph.D. from Carnegie Mellon University in computer science. His research focuses on techniques for describing, acquiring, and exploiting the semantics of data. He has worked extensively on source modeling, schema and ontology alignment, entity and record linkage, data cleaning and normalization, extracting data from the Web, and combining all of these techniques to build knowledge graphs. He has published more than 300 journal articles, book chapters, and conference papers on these topics and has received 7 best paper awards on this work. Dr. Knoblock is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), a Fellow of the Association of Computing Machinery (ACM), past President and Trustee of the International Joint Conference on Artificial Intelligence (IJCAI), and winner of the Robert S. Engelmore Award.