Hi all, I'm trying to implement a recommender based on Mahout to recommend jobs for users. There are 2 actions - an user applied for a job or viewed a job. In terms of weight I'm using 5 for an apply and 2 for a view.
Now I'm trying to find best user similarity to capture these relations. For example: User1 applied to jobs: J1,J2,J3,J4,J5 User2 applied to jobs: J1,J2,J3,J4,J6 User3 applied to jobs: J1, J7 When using Euclidean distance similarity if I'm not mistaken users 2 and 3 are equal (when calculating similarity to User1). But I feel User2 is more similar and thus J6 should be higher in the recommendations than J7. Generally, I'm looking into more suggestions what algorithms might be the best for this case. Thank you very much for any suggestions. P.
