Hi, I'm using lucene and solr right now in a production environment with an index of about a million docs. I'm working on a recommender that basically would list the n most similar items to the user based on the current item he is viewing.
I've been thinking of using solr/lucene since I already have all docs available and I want a quick version that can be deployed while we work on a more robust recommender. How about overriding the default similarity so that it scores documents based on the euclidean distance of normalized item attributes and then using a morelikethis component to pass in the attributes of the item for which I want to generate recommendations? I know it has its issues like recomputing scores/normalization/weight application at query time which could make this idea unfeasible/impractical. I'm at a very preliminary stage right now with this and would love some suggestions from experienced users. thank you, Luis Guerrero
