Television: Personalized Content Recommendation Workflow

PredictModel offers an advanced AWS-based solution to provide personalized content recommendations for television viewers. By leveraging data engineering and machine learning, we help media companies enhance user experience and maximize engagement through tailored content suggestions.

Amazon S3
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Amazon Kinesis
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Amazon DynamoDB
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Amazon Personalize
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AWS Lambda

Workflow Step Explanation

  1. Data Storage: Amazon S3 serves as the initial data lake for storing raw viewership data, including user interactions and viewing history.
  2. Data Ingestion: Amazon Kinesis streams real-time data of user activities to ensure up-to-date information is processed continuously.
  3. Data Management: Amazon DynamoDB stores and manages user profiles and metadata required for content recommendation.
  4. Machine Learning: Amazon Personalize builds, trains, and deploys personalized machine learning models to generate content recommendations based on individual user preferences.
  5. Automation: AWS Lambda automates the recommendation engine, triggering the delivery of personalized content suggestions as users interact with the platform.