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monoceros

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Data Structure and approach for recommendations system

Hi,

I am working on a simple recommendations system. Conceptually the bare bones structure (using relational database terms because thats what I am familiar with) is:

fact_table:
  score
  recommender_id
  item_id

I then want to, for a given recommender_id rank all other recommender_ids by their similarity (e.g. if recommender_id 1 scored item_id 1 as 10 and item_id 100 as 0 then another recommender ranking 1 as 9 and 100 as 1 will rank higher than a recommender scoring 10 for 1 and 8 for 100).

I expect this to be a quite large sparse matrix, possibly tens of thousands on each axis.

I would like to get the approach right from the start and would like recommendations for how to best structure the data and which language / tools to use.
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dpearson

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monoceros

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Hey, Doug,
Thanks - thats eloquent and looks straightforward (and happens to be in Java, which I do know)! For some reason I was blinkered with a view that "this is math, its big(ish) data - therefore I need one of the fancier newer languages" (partly driven by a desire to learn them!) but this is clean and can get me to a MVP without any steep language learning curve.
Cheers,
Mono.