"Knowledge base recall: detecting and resolving the unknown unknowns" by Simon Razniewski and Gerhard Weikum with Martin Vesely as coordinator

Abstract

Knowledge bases about entities like people, places and products have become key assets of search and recommender systems. The largest of them contain many millions of entities and billions of facts about them. Nevertheless, they have major gaps and limitations in what they cover, thus posing the challenge of detecting and resolving these "unknown unknowns". This paper provides an overview on the problems in mapping knowledge base recall and the existing approaches to address these issues. Specifically, we discuss i) formalisms and tools for describing incompleteness, ii) rule mining methods to assess recall, iii) text mining methods to this end, and iv) approaches towards relative recall and informativeness.