User can see recommended products

[stevebrownlee]

Bangazon Recommendation Engine

Sets

You will learn how to use unions and intersection on sets to determine if a particular customer should have certain products in their Recommendation List. What drives if a product should be recommended?

1. Did the customer like it?
2. Do other customers like it?
3. Is it in the same category as the product(s) they like?
4. Does it share a common word in the title?

Like Similarity Coefficient in Two Sets

Dislike Similarity Coefficient in Two Sets

Dislike+Like Similarity Coefficient in Two Sets

Dislike+Like Similarity+Difference Coefficient in Two Sets

Possibility Coefficient

This looks complex at first blush, but you'll discover that the steps with become clearer as you work it out.

Requirements

1. When a customer first authenticates, the first view should display two lists.
   1. If there are any items currently in an open order, display those products.
   2. List any products that have a Possibility Coefficient great than 0.25.
2. On the product detail view, add an affordance for a customer to like, or dislike, a product.
3. If a customer has ordered a product, then it should be registered as a like, regardless if the customer performed the gesture on the product detail page.

Resources

• The Jaccard similarity coefficient
• Article describing the general process, but with Node.js.