PhD Seminar • Data Systems • Autonomously Computable Information Extraction

Please note: This PhD seminar will take place in DC 1304.

Besat Kassaie, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Frank Tompa

Most optimization techniques deployed in information extraction systems assume that source documents are static. Instead, extracted relations can be considered to be materialized views defined by a language built on regular expressions. Using this perspective, we propose an efficient mechanism to identify updates for which we can autonomously compute an extracted relation. We present experimental results that support the feasibility and practicality of this mechanism in real world extraction systems.