Maintaining a high degree of user trust on System that selects the best recommendations of a product for the user

1. Which algorithm is best for recommender system?
2. What kind of information does a recommendation engine need for effective recommendations?
3. What are recommendation systems in machine learning?

Which algorithm is best for recommender system?

K-NearestNeighbor (K-NN): The K-NN algorithm is often used for recommender systems because it is able to handle large amounts of data and can produce good predictions. The K-NN algorithm works by finding the k nearest neighbours of a given item. The neighbours are then used to vote on the rating of the item.

What kind of information does a recommendation engine need for effective recommendations?

Recommendation engines also use customer attribute data such as demographics (age, gender) and psychographics (interests, values) to identify similar customers, as well as feature data (genre, item type) to identify product similarity.

What are recommendation systems in machine learning?

A recommendation system is an artificial intelligence or AI algorithm, usually associated with machine learning, that uses Big Data to suggest or recommend additional products to consumers. These can be based on various criteria, including past purchases, search history, demographic information, and other factors.