It'll use standard algorithms, although the MVP will only have one available (using pearson currently). My goal is to make various alogrithms eventually available, and perhaps some mechanism to select the best automatically (e.g., selecting the best method based on how sparse or dense the graph is).
As for bulk export, yes in the sense of "download all the calculated recommendations" (perhaps you want to dump that to a local db to access that data directly, rather than rely on hitting my api every time you need something), but not "download all the data exactly as I put it in". For the most part, the data you put into my service should already exist in your own database (what products your users have purchased, what products your users elected as liking). In addition, you'll likely want to use a one-way hash to hash sources (especially if you use usernames or email addresses to uniquely identify users).
I probably won't launch with the ability to add weights to edges, although that's probably one of the first post MVP features on my todo list.
As for bulk export, yes in the sense of "download all the calculated recommendations" (perhaps you want to dump that to a local db to access that data directly, rather than rely on hitting my api every time you need something), but not "download all the data exactly as I put it in". For the most part, the data you put into my service should already exist in your own database (what products your users have purchased, what products your users elected as liking). In addition, you'll likely want to use a one-way hash to hash sources (especially if you use usernames or email addresses to uniquely identify users).
I probably won't launch with the ability to add weights to edges, although that's probably one of the first post MVP features on my todo list.