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I've actually looked a bit at bulbflow before, being a Python programmer who has had an interest in graph databases for quite some time. That's why I asked my q

• espeed 15y ago
  These are the base elements: * Nodes/Vertices: Person, Topic, Entry * Relationships/Edges: Tagged, Authored person -- authored --> entry entry -- tagged --> topic Here's the base model: https://github.com/espeed/lightbulb/blob/master/lightbulb/model.py https://github.com/espeed/lightbulb/blob/master/lightbulb/mo... The comment system is a separate, generic component. Marko, the guy who created Gremlin (https://github.com/tinkerpop/gremlin/wiki https://github.com/tinkerpop/gremlin/wiki), just released a Gremlin Tree step (https://github.com/tinkerpop/gremlin/wiki/Tree-Pattern https://github.com/tinkerpop/gremlin/wiki/Tree-Pattern), which makes it really easy to build a threaded comment tree in one quick shot. If you have a large blog or content system, you can use likes and views to make content recommendations using a basic Gremlin collaborative filtering query: // calculate basic collaborative filtering for vertex with user_id def rank_items(user_id) { m = [:] g.v(user_id).out('likes').in('likes').out('likes').groupCount(m) m.sort{a,b -> a.value <=> b.value} return m.values() } If you use Facebook, Twitter, or GitHub to authenticate users you can easily incorporate friends and followers into the recommendations.
  • kisielk 15y ago
    Thanks for taking the time to explain, I'll definitely be doing some reading over the code.