AI0-001 AI Concepts and Foundations Practice Question
A marketing team uses a recommendation system to suggest products to customers. The system currently uses collaborative filtering. Which scenario would most likely cause the cold-start problem?
⚠ Common exam trap
CompTIA often tests the cold-start problem by making candidates confuse it with performance issues or UI changes, but the trap here is that the cold-start problem is specifically about insufficient interaction data for new users or items, not about algorithm switches or interface redesigns.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A new product is added to the catalog with no purchase history.
The cold-start problem occurs when a recommendation system lacks sufficient data to make accurate predictions. In collaborative filtering, recommendations rely on historical user-item interactions (e.g., purchase history). A new product with no purchase history has no interaction data, so the system cannot find similar users or items to generate recommendations, directly causing the cold-start problem.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A new product is added to the catalog with no purchase history.
Why this is correct
Collaborative filtering derives recommendations from user-item interaction patterns, so a product with no purchase history has no latent factor to learn from. This absence of interaction data is precisely the cold-start constraint, making the new catalogue item the scenario that triggers it.
- ✗
The system switches from collaborative filtering to content-based filtering.
Why it's wrong here
Switching to content-based filtering does not create cold-start; that method relies on item attributes and can recommend new items. It is tempting because collaborative filtering itself suffers cold-start for new users or items, so changing algorithms appears related, but the switch actually mitigates rather than causes it.
- ✗
The website interface is redesigned, affecting user navigation.
Why it's wrong here
A redesigned interface changes navigation patterns but leaves the user-item interaction matrix intact, so collaborative filtering still has ratings to work from. Interface redesigns are tempting because they alter behaviour data, yet cold-start specifically concerns absent interaction history for new users or items.
- ✗
A seasonal product experiences a sudden spike in sales.
Why it's wrong here
A seasonal sales spike supplies abundant new interaction data, which collaborative filtering exploits rather than lacks. Spikes are tempting because they shift item popularity, but cold-start requires missing user-item interactions; a surge adds them, so the model has more signal, not less.
About these practice questions
One of 962 original AI0-001 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.