Database Principles in Information Extraction

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 computa-tional challenges associated with Big Data. This tutorial gives an overview of the algorithmic concepts and techniques used for per-forming Information Extraction tasks, and describes some of the declarative frameworks that provide abstractions and infrastructure for programming extractors. In addition, the tutorial highlights op-portunities for research impact through principles of data manage-ment, illustrates these opportunities through recent work, and pro-poses directions for future research