Campus Event Calendar
Event Entry
What and Who
What knowledge bases know (and what they don't)
Simon Razniewski
MMCI
Joint Lecture Series
AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, MMCI
Public Audience
English
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Date, Time and Location
Wednesday, 4 October 2017
12:15
60 Minutes
E1 5
002
Saarbrücken
Abstract
Knowledge bases such as Wikidata, YAGO, or the Google Knowledge Graph are increasingly used in applications like entity resolution, structured search or question answering. The correctness of these knowledge bases is generally well understood and at the center of attention in automated construction techniques. About their completeness, in contrast, most knowledge is anecdotal: Completeness is usually correlated with popularity of topics, yet understanding whether a knowledge base has complete information on a specific topic is often difficult.
In this talk I will introduce the problem of understanding the completeness of knowledge bases. I will present three approaches: (i) data-inherent inferences about completeness using association rule mining, (ii) extraction of cardinality information from text sources, and (iii) various tools we developed to help knowledge base curators and consumers in mapping and understanding the completeness of knowledge bases.
In this talk I will introduce the problem of understanding the completeness of knowledge bases. I will present three approaches: (i) data-inherent inferences about completeness using association rule mining, (ii) extraction of cardinality information from text sources, and (iii) various tools we developed to help knowledge base curators and consumers in mapping and understanding the completeness of knowledge bases.
Contact
Jennifer Müller
2900
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Jennifer Müller, 08/24/2017 12:26 -- Created document.