User 3400 | 3/10/2016, 3:26:13 AM
I am presently working on Recommender systems based on click and purchase history. Basically I have the following information:
• User id • Merchant id • Number of times viewed • Number of times purchased
Total users = 16376 Total merchants = 135 Total transactions = 28,383
An interesting observation to note is that 57% of the entire dataset is covered by top 10% merchants. So it’s highly skewed.
As of now I have defined an “Affinity” as the ratio of Purchase/View and tried to come up with a recommender model. Is it possible to include Click and Purchase details to account for negative affinity?
Any suggestions would be very helpful