Data Interview Question

Video Suggestion System

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Requirements Clarification & Assessment

  1. Objective:

    • Develop a video recommendation system for a platform like YouTube.
    • Focus on enhancing user engagement and satisfaction.

  2. User Data Requirements:

    • User Profile: Age, gender, location, language, device preferences.
    • Behavioral Data: Watch history, search history, likes, dislikes, comments.
    • Interaction Data: Watch time, video completion, subscriptions.

  3. Video Data Requirements:

    • Metadata: Title, description, tags, categories, channel information.
    • Engagement Metrics: Views, likes, dislikes, comments.
    • Content Analysis: Extract topics, themes, sentiment using NLP.

  4. Performance Metrics:

    • Click-through rate (CTR), watch time, user satisfaction.
    • Number of videos saved in "watch later."
    • Number of likes on recommended videos.

  5. System Constraints:

    • Handle large-scale data efficiently.
    • Ensure low latency for real-time recommendations.

  6. Key Challenges:

    • Cold start for new users.
    • Balancing personalization with diversity.
    • Ensuring privacy and data protection.

  7. Clarifying Questions:

    • What is the primary business metric for success?
    • Are there specific categories of videos to focus on?
    • How frequently should recommendations be updated?