Practice Item-based Collaborative Filtering - 11.2.2.b | 11. Recommender Systems | Data Science Advance
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics

Grades

Grade 8 Grade 9 Grade 10 Grade 11 Grade 12

Curriculum

CBSE ICSE IB
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

games
Typing
Memory
Math
English Adventures
Knowledge

11.2.2.b - Item-based Collaborative Filtering

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take mock test.

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is item-based collaborative filtering?

💡 Hint: Think about what it means to recommend based on items rather than users.

Question 2

Easy

Give an example of an application that uses item-based collaborative filtering.

💡 Hint: Consider how you see suggestions while shopping online.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does item-based collaborative filtering focus on?

  • User similarity
  • Item similarity
  • User preferences

💡 Hint: Remember the method's name: it involves items.

Question 2

True or False: Item-based collaborative filtering is less stable than user-based filtering.

  • True
  • False

💡 Hint: Think about which type of data is more variable.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given two potential items, A and B, describe how you would determine their similarity for recommendations using item-based collaborative filtering.

💡 Hint: Consider the tools or metrics that assess multi-user engagement with both items.

Question 2

Evaluate the effectiveness of item-based collaborative filtering for a new video streaming platform just launched. What would be your approach to recommend content without existing user data?

💡 Hint: Think about how integrating different data sources can produce better outcomes.

Challenge and get performance evaluation