A generalized items recommender that lists out top 5 recommendations based on users with similar choices.
We live in a digital world with lots of online services to buy and review items, content, services, and facilities etc. One of the important things that we look for while estimating the quality of a product is throught the ratings and reviews. We spend a lot of time on websites exploring the catalog of 1000s of items, then checking the reviews and rating, filtering out the worst ratings and wishlisting the good ones.
The idea behind implementing this model is to reduce the time a user wastes on your ecommerce website and will be directly redirected to the recommended items based on your history of item ratings and a user’s shopping pattern similarities with the other users.
This model uses SVD (Singular Value Decomposition) algorithm, which creates a matrix of users x items, with their rating values, looks for patterns across the users dimension and predicts the rating for all the other items based on the rating pattern similarity with other users.
To know more visit: https://analyticsindiamag.com/singular-value-decomposition-svd-application-recommender-system/