Ronald Fagin
Discrete Mathematics
Information Extraction commonly refers to the task of populating a relational schema, having predefined underlying semantics, from textual content. This task is pervasive in contemporary computational challenges associated with Big Data. In this article we provide an overview of our work on document spanners-a relational framework for Information Extraction that is inspired by rule-based systems such as IBM's SystemT.
Ronald Fagin
Discrete Mathematics
Douglas Burdick, Ronald Fagin, et al.
ICDT 2015
Malcolm C. Easton, Ronald Fagin
CACM
Ronald Fagin, Jonathan Lenchner, et al.
LICS 2021