
Recommender Systems Concepts and Challenges
Interactive Video
•
Science
•
8th Grade
•
Practice Problem
•
Hard
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8 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main purpose of a recommender system?
To create new movies
To help people find new things based on information and social ratings
To store large amounts of data
To translate languages
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which programming language and tool are used to build the movie recommender system?
Java and Eclipse
C++ and Visual Studio
Python and Google Colaboratory
Ruby and GitHub
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
To get more reliable generic movie recommendations, what step did the presenter take after noticing many movies had perfect 5.0 ratings from only one person?
He asked his friend John Greenbot for his opinion
He filtered the movies to include only those with at least a certain number of ratings
He removed all movies with a 5.0 rating
He changed the rating scale from 1-5 to 1-10
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the "cold-start problem" for a recommender system?
The system recommends movies that are too old
The system cannot make personalized recommendations without enough user data
The system takes too long to load
The system recommends movies that are not popular
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary purpose of the AI being programmed?
To categorize movies by genre
To provide personalized movie recommendations
To analyze movie production budgets
To create new movie scripts
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a likely outcome when the AI uses a small neighborhood size for recommendations?
It will recommend only very popular movies
It will suggest more surprising or obscure movies
It will consider many people with diverse tastes
It will have more data to make accurate predictions
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a likely outcome when the AI uses a large neighborhood size for recommendations?
It will recommend movies tailored to individual interests
It will suggest movies that are generally popular and widely known
It will have less data to make predictions
It will only consider people with very similar movie tastes
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