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Knowledge engineering: from people to machines and back
Published on Jun 13, 202485 Views
Knowledge engineering is about building and maintaining knowledge-based systems. As a field, it occupies a unique niche between software engineering, which involves crafting software that represents k
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Chapter list
Knowledge engineering: from people to machines and back00:00
Knowledge engineering02:45
Knowledge engineering: Before05:02
Knowledge engineering: Today06:49
My KE journey08:52
Standard knowledge engineering process during my PhD09:37
Case studies, guidance, templates to reuse ontologies effectively10:23
Predicting costs, understanding the most resource-intensive part of the process13:09
Two ways forward14:29
Two challenges15:45
Participation: aligning tasks to people’s motivations, designing incentives16:36
People implicitly contribute to the knowledge base while going about their regular work18:03
People play games. Games data is turned into computational knowledge19:49
People are part of online communities that build knowledge bases21:04
What if automation were an option?22:56
Knowledge integrity in Wikidata24:26
Are references easy to navigate, authoritative, relevant?25:14
Does the source support the claim?26:12
Chandler Fashion Center27:46
William Sleator28:05
Gideon28:24
Robert Brunton28:34
InterServe28:44
Tegaserod28:50
James Billington28:54
Datasets30:08
Complex task, 87.5% accuracy when explicit textual evidence present31:05
What’s next31:54
Ontology Engineering33:58
We are now at that stage ...34:25
Dagstuhl seminar 09/2236:24
Hackathon 08/2337:09
Call for papers37:44
How do knowledge engineers use LLMs38:05
Findings39:00
LLMs and requirements engineering40:22
Example: OntoChat40:57
User research: mock-ups41:18
Using LLMs and knowledge graphs to reverse engineer competency questions41:51
Explanations42:22
Cards for KGs and KG embeddings42:53
Final thoughts43:08
Where is the web in all this?44:42
Thank you45:36