The answer was not the point. The answer was never the point. The process of searching is the process of learning.

The query above is a short one liner in Cypher but can be completely unreadable in SQL

Well in general finding people united by chain of relationships. For example, who are the doctors that assessed all the claimants that have the same solicitor as claimant 2

It makes things easier, though of course almost anything can be built on top of a relational database

One can efficiently build queries for next nearest neighbours of higher orders as well as match specific edges

There's at least two steps: 1) find nodes with highest centrality score and tag them as :CENTRAL 2) match nearest neighbours. Step 1 can be accomplished by a plugin in neo4j. Step 2 could be something like MATCH (:CENTRAL)-[]->(nn) in neo4j Cypher.

Within fraud detection, graphs can quickly provide information about which actor is central to frauds, and who is near them. Graph-dbs allow for a large number of entities to be memorised and processed.

Thank you this is great to hear

We do. Sooner or later, it will land on our YouTube channel www.youtube.com/playlist?lis...

What a fantastic guest! Do you have recordings?

This reminds me a colleague from est Glasgow that pointed out he was technically "middle aged" at 27

If we got this method to work, the payoff might be that we could measure uncertainty, and distant-read things like the history of the cliffhanger.

The hound of the Baskerville's was published in the strand originally. One can find the scanned pages here www.dfw-sherlock.org/uploads/3/7/...

I understand better now. I bet someone already made a corpus with the original installments

Sherlock Holmes collected stories are out of copyright. For example sherlock-holm.es/pdf/letter/1...