UTCS AI Colloquia - Craig A. Knoblock, University of Southern California, "Creating and Using Linked Knowledge"
Signup Schedule: http://apps.cs.utexas.edu/talkschedules/cgi/list_events.cgi
Talk Audience: UTCS Faculty, Grads, Undergrads, Other Interested Parties
Host: Dan Miranker
Talk Abstract: Companies, such as Google and Microsoft, are building web-scale linked knowledge bases for the purpose of indexing and searching the Web, but these efforts do not address the problem of building accurate, fine-grained, deep knowledge bases for specific application domains. We are developing an integration framework, called Karma, which supports the rapid, end-to-end construction of such linked knowledge bases. In this talk I will describe machine-learning techniques for mapping new data sources to a domain model and present an application of this technology to build a virtual museum of American art.
Speaker Bio: Craig Knoblock is a Research Professor of Computer Science and Spatial Sciences at the University of Southern California (USC) and the Director of Information Integration at the USC Information Sciences Institute. He received his Ph.D. in computer science from Carnegie Mellon. His research focuses on techniques related to information integration, Semantic Web and Linked Data. He has published more than 250 journal articles, book chapters, and conference papers. Dr. Knoblock is a AAAI Fellow, a Distinguished Scientist of the ACM, and past President and Trustee of IJCAI. He was selected for the 2014 Robert S. Engelmore Award for his contributions to applied AI. He and his co-authors were recognized for the Best Research Paper at ISWC 2012 on Discovering Concept Coverings in Ontologies of Linked Data Sources and the Best In-Use Paper at ESWC 2013 on Connecting the Smithsonian American Art Museum to the Linked Data Cloud.
- Awards & Honors
- About Us
- Student Engagement and Support
- Masters Program
- Ph.D. Program
- Financial Information
- Prospective Students
- Incoming Students
- Current Students
- Portfolio Program in Robotics
- Curricular Practical Training
- Grad Student Talks
- UTCS Direct