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Knowledge Representation and the Semantic Web – an Ontologician´s View

Published on Jul 10, 2018747 Views

Sebastian Rudolph

With the rise of the Semantic Web and in the course of the standardization of ontology languages, logic-based knowledge representation (KR) has received wide attention from academics and practitioners

ESWC 2018 - Heraklion

Related categories

Big DataSemantic Web

Chapter list

Knowledge Representation and the Semantic Web – an Ontologician's View00:00
(1) G(r)eek Joke (2) Anecdote - 101:11
(1) G(r)eek Joke (2) Anecdote - 202:19
Purpose of the Talk03:18
Facts about Logicians05:14
Gottfried Wilhelm Leibniz (1646 Sebastian Rudolph ESWC 2018 Slide 7 -1716) 06:53
formal definition of syntax and semantics of logics and deduction calculi establish foundations for automated inferencing07:46
rise of computers and research on symbolic AI and deductive databases pave way toward automated reasoning - 109:01
Evolution: Mathematical Logic  Computational Logic09:17
more and more knowledge is available in interlinked, structured, logically accessible form, providing ground truth about the world10:00
Evolution: Classical KR  Contemporary KR10:23
Convergence of KR and Databases - 110:48
Convergence of KR and Databases - 213:58
Challenges for Logic-based KR15:47
Research Workflow for Logic-based KR - 117:50
Research Workflow for Logic-based KR - 219:24
Research Workflow for Logic-based KR - 320:20
Identification of Novel Logical Features20:29
Example: Modeling Feature - 122:11
Example: Modeling Feature - 223:47
Research Workflow for Logic-based KR24:56
Investigation of Computational Properties25:03
Example: Simple Conjunctive Queries in OWL26:57
The Problem28:10
Part I: Testing for K ² q28:46
How to Test for K ²/ q ?29:45
Proof of Representativity: Overview30:50
Part II: Testing for K ² q31:32
The “Algorithm“32:05
Many Open Problems...33:20
Post Correspondence Problem34:06
Post Correspondence Problem - 234:40
Post Correspondence Problem - 335:13
Post Correspondence Problem - 435:15
Post Correspondence Problem - 535:17
Post Correspondence Problem - 635:22
Post Correspondence Problem - 735:39
Post Correspondence Problem - 835:44
Post Correspondence Problem - 935:48
Post Correspondence Problem - 1036:03
Post Correspondence Problem - 1136:12
Post Correspondence Problem - 1236:23
Digression: State of Decidability - 137:10
Digression: State of Decidability - 238:46
A Grand Unified Theory of Decidability in Logic-Based Knowledge Representation39:03
Untitled39:23
Research Workflow for Logic-based KR - 239:32
Algorithm Design39:33
Example: OWL QL Query Answering - 140:12
Example: OWL QL Query Answering - 240:33
Example: OWL QL Query Answering - 340:50
Example: OWL QL Query Answering - 441:17
Example: OWL QL Query Answering - 541:39
Example: OWL QL Query Answering - 641:55
Example: OWL QL Query Answering - 742:08
Example: OWL QL Query Answering - 842:11
Example: OWL QL Query Answering - 942:23
Example: OWL QL Query Answering - 1042:58
Example: OWL QL Query Answering - 1143:13
Example: OWL QL Query Answering - 1243:38
Example: OWL QL Query Answering - 1343:39
Research Workflow for Logic-based KR - 143:53
Research Workflow for Logic-based KR - 244:00
Why Modeling Support? - 144:05
Why Modeling Support? - 245:00
Why Modeling Support? - 345:29
Modeling Support: Guided KB Completion46:03
Modeling Support: Possible World Explorer - 146:11
Modeling Support: Possible World Explorer - 246:49
Further Challenges I: Noise47:21
Further Challenges II: Dynamics48:20
Conclusion & Credo49:17