Practice Explainable Recommendations (11.9.4) - Recommender Systems - Data Science Advance

Practice: Explainable Recommendations

Lesson 11.9.4Recommender Systems

Practise this section

9 questions

Flashcard drill
4 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is explainable recommendations?
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Think about the purpose of recommendations in aiding decision-making.
Question 2.
Give an example of rule-based explanations.
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Consider how systems connect previous choices to new suggestions.
3Question 3.
What is the main benefit of explainable recommendations?
- Increased sales
- Greater user trust
- Faster algorithm performance
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Consider the role of understanding in the decision-making process.
4Question 4.
True or False: Feature highlighting involves showing how other users have liked an item.
- True
- False
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Think about what 'feature' means in this context.
Question 5.
Create an explainable recommendation for a music streaming service based on user preferences and behaviors.
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Think deeply about the connections that can be made between past user behavior and their current suggestions.
Question 6.
Discuss how a lack of explainable recommendations could potentially harm user satisfaction in a shopping website.
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Reflect on personal experiences with apps that made recommendations without clarification.

5 more questions in this section. Enroll free to practise them all.