Monday, December 16, 2019
1400 Wegmans Hall
Rochester Institute of Technology
Fast Discovery of Nested Dependencies on JSON Data
Data dependencies and algorithms to mine them provide significant insight into unfamiliar datasets with limited metadata. They can be used to help identify constraints such as primary and foreign keys. Existing algorithms have focused primarily on mining dependencies from relational databases. Little attention has been paid to the explosion of semi-structured data from web services and NoSQL databases. This talk highlights some of the problems with existing approaches and presents new dependency structures and mining algorithms to handle this data.
Michael J. Mior received an MSc degree from the University of Toronto in 2011. After spending a few years at a startup company, he received his PhD from the University of Waterloo in 2018. Michael then joined the Computer Science Department at the Rochester Institute of Technology as an Assistant Professor. His research interests include schema design, understanding, and integration for non-relational semi-structured data.