Chapter 7 Part 1

What is the primary goal of a recommendation system?

• Classify emails

• Find missing values

• Suggest relevant items to users

• Remove outliers

Which of the following is a common use of recommendation systems?

• Predicting weather

• Detecting anomalies

• Product recommendations in e-commerce

• Clustering genes

Which type of data is used by recommendation systems to make suggestions?

• Only explicit data

• Only implicit data

• Both explicit and implicit data

• Only labeled data

What is “explicit data” in recommendation systems?

• User’s age

• Purchase history

• User ratings and reviews

• Search queries

What is “implicit data” in recommendation systems?

• Ratings given by users

• Browsing history and clicks

• User feedback surveys

• Movie genres

Which of these is NOT an example of a recommendation system?

• Netflix movie suggestions

• Google search autocomplete

• Amazon product recommendations

• Spotify playlist suggestions

What is content-based filtering?

• Recommendations based on friends' choices

• Suggestions based on user’s past preferences and item features

• Grouping users by region

• Sorting products by price

What is collaborative filtering?

• Uses only item features

• Ignores user data

• Recommends items by finding similar users or user-item interactions

• Focuses only on explicit ratings

Which of these platforms uses recommendation systems?

• Facebook

• YouTube

• TikTok

• All of the above

Which of the following is an advantage of using recommendation systems in e-commerce?

• Slower purchase process

• Reduced customer satisfaction

• Increased sales and conversions

• More customer churn