Hi: In paper "Item-Based Top-N Recommendation Algorithms"(https://stuyresearch.googlecode.com/hg/blake/resources/10.1.1.102.4451.pdf), there are two parameters measuring the quality of recommendation: HR and ARHR. If I use ALS(Implicit) for top-N recommendation system, I want to check it's quality. ARHR and HR are two good quality measures. I want to contribute them to spark MLlib. So I want to know whether this is meaningful?
(1) If n is the total number of customers/users, the hit-rate of the recommendation algorithm was computed as hit-rate (HR) = Number of hits / n (2)If h is the number of hits that occurred at positions p1, p2, . . . , ph within the top-N lists (i.e., 1 ≤ pi ≤ N), then the average reciprocal hit-rank is equal to: [cid:image001.png@01CFC086.8EE1FF40]i .
