Build your own Recommendation Engine with Neo4j and Reco4PHP

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Anonymous at 11:50 on 24 Jun 2016

Interesting demo to see the systems work, but it's missing a bit of background on alternatives and the pros and cons of each.

Colin O'Dell at 12:01 on 24 Jun 2016

I would've liked to hear more about why Reco4PHP is better than using Neo4j directly - for example, are there certain issues or pain points which the library overcomes?

I think it would've also been helpful to spend a minute describing the Cypher queries for those with little/no prior experience.

Nevertheless, I did learn a good bit from this talk and look forward to playing with the library in the future.

Boy Baukema at 14:32 on 24 Jun 2016

Would've like more info on Neo4j and in depth info on Cypher queries.

Ron Rademaker at 22:45 on 24 Jun 2016

Good talk, speaker knows what he's talking about but should get some more experience and should work on his English pronunciation. Good speed for me, happy we didn't linger at code details for a query language I'd need to learn from scratch anyway. Too bad I think some people got scared off at the end with the money question, I was convinced enough to give it a try with the community open source edition.

Interesting talk, the speaker did know what he was talking about. However wIth some more experience in speaking i am sure the talk would be better.

Very good intro to using neo4j in general. The PHP Library looks interesting.

Thomas Los at 23:30 on 25 Jun 2016

Great talk, inspiring for a graph novice as myself, can't wait to get started.

Interesting topic, not the best talk though. I think it needs some work on the structure and the content. For example: it was confusing that at one point we were talking about LinkedIn and a minute later about Github, as an example. It might be better to pick one example and stick by it.

Got me looking into graph databases though, so thanks for that! :)

Nice introduction into graph querying, Neo4J and it's PHP adapter Reco4PHP.

Arnout Boks at 09:09 on 23 Jul 2016

Nice introduction to graph databases and recommendation engines. Would have appreciated a bit more general theory/background than some hasty usage examples of one particular library.