It's an average similarity, weighted by count -- which is to say, it's a sum of similarities. This isn't terribly principled but works reasonably in practice. A simple average tends to over-weight unpopular items, but there are likely better ways to account for that.
On Thu, Nov 15, 2012 at 5:59 PM, Pat Ferrel <[email protected]> wrote: > Using a boolean data model and log likelihood similarity I get > recommendations with strengths. > > If I were using preference rating magnitudes the recommendation strength > is interpreted as the likely magnitude that a user would rate the > recommendation. Using the boolean model I get values approaching 2 (this > over a quick and small sample so not sure of the real range), which leads > me to the question... > > What is the meaning of the strength returned with the recommendation for > boolean data?
