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What and Who
Title:Digital Knowledge: From Facts to Rules and Back
Speaker:Daria Stepanova
coming from:Max-Planck-Institut für Informatik - D5
Speakers Bio:
Event Type:Joint Lecture Series
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
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Level:Public Audience
Date, Time and Location
Date:Wednesday, 3 May 2017
Duration:60 Minutes
Building:E1 5
Knowledge Graphs (KGs) are huge collections of primarily encyclopedic facts, which are automatically extracted from the Web. Prominent examples of KGs include Yago, DBPedia, Google Knowledge Graph. We all use KGs when posing simple queries like "capital of Saarland" to Google. Internally, such queries are translated into machine readable representations, which are then issued against the KG stored at the backend of the search engine. Instead of syntactically relevant Web pages, the actual answer to the above query, "Saarbrücken", is then output to the user as a result.

However, since KGs are automatically constructed, they are often inaccurate and incomplete. In this talk, I will investigate how deductive and inductive reasoning services could be used to address these crucially important issues. More specifically, first, I will present an approach for repairing inconsistencies in hybrid logical systems that can be built on top of KGs. Second, I will describe a method for inductive learning of rules with exceptions from KGs and show how these are applied for deriving missing facts.
Name(s):Jennifer Müller
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:NoTo Location:
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Attachments, File(s):
Jennifer Müller/MPI-INF, 02/21/2017 01:26 PM
Last modified:
Uwe Brahm/MPII/DE, 05/03/2017 07:01 AM
  • Jennifer Müller, 04/26/2017 04:27 PM
  • Jennifer Müller, 02/21/2017 01:28 PM -- Created document.