Recommendation Algorithm Analysis

Item to Item Rating based on customer’s purchase of products

The formula for comparison is dot product divided by product of vector lengths
In the example for two sets Book and DVD

• Book – (1,1,1) – Set A consider it as (A1, A2, A3)
• DVD – (1,0,0) – Set B consider it as (B1, B2, B3)

Formula works as

• (A1.B1 + A2.B2 + A3.B3) /sqrt((A1 square + A2 Square + A3 Square)( B1 square + B2 Square + B3 Square))
• (1)/sqrt((3).sqrt(1)
• 1 / 1.732
• 0.577

     Item to Item Comparison based on customer ratings

The formula for comparison is dot product divided by product of vector lengths

In the example for two sets Book and DVD

• Book – (4,3,5) – Set A consider it as (A1, A2, A3)
• DVD – (1,0,0) – Set B consider it as (B1, B2, B3)

Formula works as 

• (A1.B1 + A2.B2 + A3.B3) /sqrt((A1 square + A2 Square + A3 Square)( B1 square + B2 Square + B3 Square))
• (4)/sqrt((16+9+25).sqrt(1)
• 4/7.07
• 0.565

Analysis - By comparing multiple items the items that yield the maximum value would be recommended to the customer

Happy Learning!!!