Scenario You are tasked with designing and implementing an e-commerce platform that includes a robust recommendation system. The goal is to suggest products to users based on their browsing and purchase history, thereby enhancing the user experience and promoting relevant products. The system needs to efficiently handle large amounts of data and provide personalized recommendations. Requirements - Personalized product recommendations based on user browsing and purchase history. - Provide relevant product suggestions. - Use at least two different data structures, including at least one non-linear data structure. Hint: Data Structures that can be used but not restricted to. 1. Hash Tables: For fast lookups of user and product data. 2. Graphs or Trees (Non-Linear Data Structure): For managing the recommendation logic and relationships between products and users
System Components
User Management: Handle user registration, login, and profile management. Product Management: Manage product information, categories, and inventory. Browsing History Tracker: Track and store user browsing history. Purchase History Tracker: Track and store user purchase history. Recommendation Engine: Analyze browsing and purchase data to generate personalized recommendations. Operations Needed
To efficiently manage these components, the system should support the following operations:
Add User: Register a new user. Add Product: Add a new product to the catalog. Track Browsing History: Record user interactions with products. Track Purchase History: Record user purchases. Generate Recommendations: Suggest products to users based on their history. Retrieve User Data: Access user data for personalized experiences. Retrieve Product Data: Access product data for displaying recommendations. Development Plan
- User Management
Data Structure: Hash Table
Operations:
Add user
Retrieve user information
Update user information
- Product Management
Data Structure: Hash Table
Operations:
Add product
Retrieve product information
Update product information
- Browsing and Purchase History Tracking
Data Structure: Graph or Tree
Operations:
Record browsing history
Record purchase history
Retrieve history for analysis
- Recommendation Engine Data Structure: Graph or Tree
Operations:
Analyze user data to identify patterns
Generate personalized recommendations based on identified patterns
Implementation
User Management Module:
Implement a hash table to store user data.
Provide functions for adding, retrieving, and updating user information.
Product Management Module:
Implement a hash table to store product data.
Provide functions for adding, retrieving, and updating product information.
Browsing and Purchase History Module:
Implement a graph or tree to track user interactions with products.
Record each browsing and purchase event in the data structure.
Provide functions to retrieve and analyze the history data.
Recommendation Engine:
Implement algorithms to analyze the browsing and purchase history data.
Use the graph or tree structure to identify patterns and relationships between users and products.