That's cool. Why do you use two algos together? Like why not just Graperank?
Discussion
I want to compare and contrast those two algos so I can better appreciate their relative strengths and weaknesses. Also, I’m using the FOSS graph database neo4j and neo4j graph data science which makes calculation of PageRank as easy as execution of a single cypher query, so no reason not to.
I do believe that GrapeRank is ultimately going to be better for most applications. It allows you to incorporate data from any source whatsoever (zaps, ratings, attestations, etc), calculate different types of scores for different contexts, tally trust-weighted votes and do weighted averages. Most importantly, it’s designed to tailor your WoT to the preferences, beliefs, and values of the end user. Over the past week I’ve figured out how to tweak some of the GrapeRank parameters to do a better job of stratification. It will improve further once I incorporate kind 1985 reports.
Very interesting. I'm currently running memgraph with their pagerank implementation but it's quite garbage. And yes a personalized view of the network is a must.
Is Graperank something you designed or it was an established algo previously?
My design. I’d love to find that someone has already implemented it bc I hate to reinvent the wheel, but if a similar centrality algo already exists, I have not yet found it.
What are the problems you’re running into with memgraph?
The biggest headache with neo4j is dealing with java garbage collection, but that’s not an insurmountable problem, just a bit of a learning curve. Other than that I’ve been happy with it. Getting a list of followers is instantaneous, something unthinkable with sql. Finding the shortest path between pubkey1 and pubkey2, is also pretty much instantaneous, even when they’re 7 or 8 hops away.
Oops, meant to say kind 1984.