Entities and Attributes in Recommendation Systems
Entities in a Recommendation System represent various aspects of users, items, interactions, and recommendations, while attributes describe their characteristics. Common entities and their attributes include:
User Profile
- UserID (Primary Key): Unique identifier for each user.
- Name, Email, Age: Demographic information of the user.
- Preferences: User preferences and interests (e.g., favorite genres, categories).
Item
- ItemID (Primary Key): Unique identifier for each item available for recommendation.
- Title, Description: Information about the item (e.g., title, description, category).
- Attributes: Additional attributes such as genre, price, release date.
Interaction
- InteractionID (Primary Key): Unique identifier for each user-item interaction.
- UserID (Foreign Key): Reference to the user involved in the interaction.
- ItemID (Foreign Key): Reference to the item involved in the interaction.
- Action: Type of interaction (e.g., view, like, purchase).
- Timestamp: Date and time of the interaction.
How to Design Database for Recommendation Systems
Recommendation systems have become important in modern digital platforms, guiding users to relevant content, products, or services based on their preferences and behavior.
Behind the effectiveness of recommendation algorithms lies a well-designed database architecture capable of storing, organizing, and analyzing vast amounts of user and item data.
In this article, we will explore the essential principles of designing databases specifically for Recommendation Systems.