This project aims to create a web application that collects product information from various online stores and performs several operations on the collected data. The application will allow users to:
- View all collected data: A main page will display all the scraped product information, including a section for product recommendations based on search history.
- Apply sorting and filtering: Users can sort and filter the products based on various criteria, such as keywords, store origin, and price.
- Access product details: Each product will have a dedicated page that displays more detailed information. This page will also include recommendations for similar products.
- Search history: Every viewed product will be added to the user's search history, which will be used to generate personalized product recommendations.
- Django: The backend framework for building the web application.
- Beautiful Soup: For web scraping to extract product data from various online stores.
- Whoosh: A fast, pure-Python search engine library for indexing and searching the collected data.
- Recommendation Systems: For providing personalized product recommendations based on user behavior.
- Data Collection: Scrapes product information from multiple online stores.
- Data Storage: Stores the scraped data in a structured format for efficient querying.
- Search Functionality: Allows users to search for products using keywords, filters, and sorting options.
- Product Details: Provides detailed information for each product, including images, descriptions, and prices.
- Recommendation System: Generates personalized product recommendations based on user search history and product similarity.
- User Interface: A user-friendly web interface for interacting with the application.
Note: This is a basic outline of the project. Specific implementation details will vary based on the chosen technologies and the complexity of the target online stores.