From the description:
OpenCredo discusses Opigram: a social recommendation engine
In this webinar, Nicki Watt of OpenCredo presents the lessons learned (and being learned) on an active Neo4j project: Opigram. Opigram is a socially oriented recommendation engine which is already live, with some 150k users and growing. The webinar will cover Neo4j usage, challenges encountered, and solutions to these challenges.
I was scheduled to watch it live but it conflicted, unexpectedly, with nap time.
Watching it now and it is very impressive!
Lots of details and code!
Some specific points that I found interesting:
- Know what questions you are going to ask the graph
- Important things => nodes (can you say subjects?)
- batch deleting (experiment with # of nodes) (Is this still an issue?)
- reservoir sampling algorithm (you need to look deeply at this)
- multi-threading fixed in 1.7 or later (issue discovered by profiling but should profile in any case)
Curious about your thoughts on the deletion issue?
On one hand, you can do “soft deletes” as discussed in this presentation but at some point, that may have an adverse impact on graph size and complexity.
On the other hand, “actual” deletion seems to be disfavored.
But change (read deletion/update) is a fact of enterprise data. (data generally but it sounds more impressive to say “enterprise data.”)