Recommendation Systems Quiz

What is the purpose of recommendation systems according to the learning material?

• To decrease company's profit

• To increase company's profit

• To collect user data

• To provide entertainment to users

How many users are there in the example provided for recommendation systems?

• 4

• 5

• 6

• 7

How many items are there in the example provided for recommendation systems?

• 4

• 5

• 6

• 7

What does each user provide for the items in the recommendation system example?

• A written review

• A rating

• A comment

• A like or dislike

What is the rating given by User 1 for Item 102?

• 2.0

• 2.5

• 3.0

• 5.0

Which item received a rating of 5.0 from User 3?

• Item 101

• Item 104

• Item 105

• Item 107

What is the main aim of user-based recommendation algorithms?

• To generate recommendations based on the highest rated items by all users

• To generate recommendations for a target user 'u' by considering the preferences of all other users

• To predict the total number of items a user will rate in the future

• To provide a static list of popular items to every user

How does the user-based recommendation algorithm compute preference for items?

• By taking the average rating of all items rated by the target user

• By considering the preferences of users who have not rated any items

• By weighting the preferences of similar users to the target user 'u' by a similarity score 's'

• By assigning random weights to the preferences of all users

What does the running average in the user-based recommendation algorithm keep track of?

• The total number of items rated by the target user

• The average similarity score between all users

• The predicted preference of the target user 'u' for item 'i'

• The number of items not yet rated by the target user

What is the end result of a user-based recommendation algorithm?

• A static list of items that are popular among all users

• A personalized set of recommended items for the target user 'u'

• The exact future ratings a user will give to unrated items

• A ranking of users based on their similarity to the target user