What is a Recommender System?

• A system that predicts future interests of users based on past behavior.

• A system for inventory management.

• A system for calculating sales tax.

• None of the above.

Which of the following is NOT a type of Recommender System?

• Collaborative Filtering

• Content-Based Filtering

• Random Selection

• Knowledge-Based Filtering

What is the Cold Start problem in recommender systems

• When the server takes too long to start.

• The challenge of recommending new items or to new users with no prior data.

• Lack of electricity for the system.

• None of the above.

Which type of recommender system relies on the attributes of items?

• Collaborative Filtering

• Content-Based Filtering

• Random Walk

• Association Rules

What is the purpose of Hybrid Recommender Systems?

• To combine two or more recommendation methods to improve accuracy.

• To recommend products with the highest price.

• To only use collaborative filtering.

• To generate random recommendations.

What are User-Based Collaborative Filtering systems focused on?

• Finding items similar to the ones a user liked.

• Finding users with similar preferences to make recommendations.

• Matching product features to user preferences.

• None of the above.

Which metric is used to measure the accuracy of a recommender system?

• Precision

• Recall

• Mean Absolute Error (MAE)

• All of the above

Which of the following best describes Serendipity in recommender systems?

• Providing expected recommendations

• Providing surprising yet enjoyable recommendations

• Providing the most expensive items

• Providing irrelevant recommendations

What is the main disadvantage of a Content-Based Recommender System?

• The system needs a large amount of user interaction data.

• It can lead to a narrow range of recommendations (filter bubble).

• It is unable to recommend new items.

• It is always computationally slow.

Which of the following is an advantage of Knowledge-Based Recommender Systems?

• They do not suffer from cold start problems.

• They always require ratings.

• They depend on collaborative interactions.

• They use probabilistic models.