Knowledge Graphs - Computerphile
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Published 2022-09-07
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This video was filmed and edited by Sean Riley.
Computer Science at the University of Nottingham: bit.ly/nottscomputer
Computerphile is a sister project to Brady Haran's Numberphile. More at www.bradyharan.com/
All Comments (21)
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take a shot everytime she says Bush house
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Our company processes unstructured CV data to make it structured. Obvious if you're in the HR industry. We were sued by IBM for patent infringement on processing "unstructured CV data" 10 years ago, when we had prior art years before their patent. Just ridiculous and left a disdain towards IBM. With the advent of AI and machine learning, hopefully this type of trolling doesn't occur as often.
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If anyone is interested in visualising graphs, I wrote an application called Graphia for this purpose. Its main use is in biological sciences, but it's designed to be general purpose.
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Great to see that kind of paper she drew on, still exists! Haven't seen it in decades. 😀
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About 30 years ago I used to setup a database system called Vineyard that came from Finland I think. It was all about building relationships between objects graphically. It let you discover interesting relationships and connections you couldn’t otherwise see.
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This was very interesting to learn about the data structure itself, but is there a good source (preferably video, but the format doesn't matter too much) to learn about how a knowledge graph is populated in the first place? That's a pretty vital bit of information that I don't know.
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EXACTLY WHAT I NEEDED! Had been looking into ontology and KGs for the past few days for an NLP project and I am going for it :)
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Nicely explained and pleasant to listen to. Can you take this further for us? ♡
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My god, I am in love with the way she says ‘knowledge graphs’.
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Is there an open source code that creates knowledge graph 📉 out of a given data? No matter whether a text, pics or video or tables?
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as person who works with Tigergraph and Neo4j i like this video
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This method seem to suck when you look something fringe stuff that has more popular "synonyms". In those cases it's not uncommon that Google completely ignores a word or two from the search to steer it toward something more popular.
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I'm not quite sure this explanation works well enough without explaining a bit more about ontologies in the first place. I've been working with RDF and related stuff for quite a bit in an enterprise PLM context, and I wouldn't have seen a knowledge graph as an AI building block - but maybe my thinking is a bit off... I might also have mentioned a few of the upsides and downsides of practical work with a knowledge graph, but I guess this is a bit too specific for an intro video.
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would like to know whether this is also called a data model. if not what are the differences between a data model and a Knowledge Graph?
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just started playing around with Dgraph/GraphQL. Dgraph has an entirely free cloud starter if anybody wants to tinker. (Not for those unfamiliar with querying databases.)
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Just want to put in a plug for Obsidian Notes if anyone wants to play with building their own knowledge graph! Just started using it and it's really cool
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How do companies like Google and others that have huge amount of this data make sure that they don't get two or more edges with different labels that reference the same data? For example, let's the underlying relationship is "location", but for LSE the edge is labelled "located in" and for KCL "location"? If that were the case they couldn't effectively query it anymore right.
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where do you still get those dot-matrix printer papers?
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Love the subtle Python reference. Tip of the cap.
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thank you so much 🥰
