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I'm not sure if I missed out any point but think below text in /doc/sar.md page needs some corrections/revisions:
################## SAR DOC
Note that the recommendation score of an item is purely based on its similarity to Item 5 in this case (??seems like duplication to some texts below). Assuming that a same item is not recommended again, items 1 and 4 have the highest score (Did you mean items 4 and 5? User already seen item 1) and would be recommended before items 2 and 3 (??).
Now, if this user adds Item 2 (Was this meant to be item 5?) to the shopping cart, affinity vector (assuming weight 2 (weight 1?) for this transaction) will be
New User aff
Item 1 0
Item 2 0
Item 3 0
Item 4 0
Item 5 1
resulting in recommendation scores:
New User rec
Item 1 2
Item 2 1
Item 3 1
Item 4 2
Item 5 3
Note that the recommendation score of an item is purely based on its similarity to Item 5 in this case. Assuming that a same item is not recommended again, items 1 and 4 have the highest score and would be recommended before items 2 and 3. Now, if this user adds Item 2 to the shopping cart, affinity vector (assuming weight 2 for this transaction) will be
New User aff
Item 1 0
Item 2 2
Item 3 0
Item 4 0
Item 5 1
resulting in recommendation scores:
################################
Thanks,
The text was updated successfully, but these errors were encountered:
Hi,
I'm not sure if I missed out any point but think below text in /doc/sar.md page needs some corrections/revisions:
################## SAR DOC
Note that the recommendation score of an item is purely based on its similarity to Item 5 in this case (??seems like duplication to some texts below). Assuming that a same item is not recommended again, items 1 and 4 have the highest score (Did you mean items 4 and 5? User already seen item 1) and would be recommended before items 2 and 3 (??).
Now, if this user adds Item 2 (Was this meant to be item 5?) to the shopping cart, affinity vector (assuming weight 2 (weight 1?) for this transaction) will be
New User aff
Item 1 0
Item 2 0
Item 3 0
Item 4 0
Item 5 1
resulting in recommendation scores:
New User rec
Item 1 2
Item 2 1
Item 3 1
Item 4 2
Item 5 3
Note that the recommendation score of an item is purely based on its similarity to Item 5 in this case. Assuming that a same item is not recommended again, items 1 and 4 have the highest score and would be recommended before items 2 and 3. Now, if this user adds Item 2 to the shopping cart, affinity vector (assuming weight 2 for this transaction) will be
New User aff
Item 1 0
Item 2 2
Item 3 0
Item 4 0
Item 5 1
resulting in recommendation scores:
################################
Thanks,
The text was updated successfully, but these errors were encountered: