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How to Build an AI News Aggregator with Community-Driven Insights and Personalized Summaries

Develop a web-based AI news aggregation platform that provides weekly email summaries, tracks AI themes over time, and incorporates community-driven insights. The system will learn from user interactions, offer customizable privacy settings, and feature a web interface for viewing past summaries and trending topics.

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Simple Summary

This coding plan outlines the development of a community-driven AI news aggregation platform with weekly email summaries, a web interface for viewing past summaries, and features for tracking AI themes over time.

Product Requirements Document (PRD)

Goals:

  1. Create an AI news aggregation platform focused exclusively on AI developments
  2. Provide weekly email summaries of AI news
  3. Develop a web interface for viewing past summaries and managing content
  4. Implement a system for tracking and categorizing AI themes over time
  5. Incorporate community-driven insights and trending topics
  6. Learn from user interactions to personalize content
  7. Allow multiple users to sign up and access the platform

Target Audience:

  • Individuals interested in staying informed about AI developments
  • US-based users with interest in global AI news when relevant

Key Features:

  1. Weekly email summaries of AI news
  2. Web interface for viewing past summaries and managing content
  3. Categorized lists for tracking AI themes over time
  4. Automatic generation and updating of AI theme categories
  5. Manual category editing capability for users
  6. Personalized content based on user interactions
  7. Commentary on potential impact of major AI developments
  8. User profiles with customizable privacy settings
  9. Trending topics and key themes based on community engagement
  10. Option for users to sign up for email summaries

User Requirements:

  • Ability to view AI news summaries on a web interface
  • Option to receive weekly email summaries
  • Customizable user profiles and privacy settings
  • Access to trending topics and community-driven insights

User Flows

  1. User Sign-up and Profile Creation:

    • User visits the platform
    • Clicks on "Sign Up" button
    • Enters personal information and creates account
    • Sets privacy preferences and email notification settings
    • Completes profile creation

  2. Viewing Weekly AI News Summary:

    • User logs into their account
    • Navigates to the "Weekly Summary" section
    • Views the latest AI news summary
    • Interacts with categorized themes and trending topics
    • Optionally clicks on specific articles for more details

  3. Customizing Theme Categories:

    • User logs into their account
    • Navigates to the "Theme Categories" section
    • Views automatically generated categories
    • Clicks on "Edit Categories" button
    • Adds, modifies, or deletes custom categories
    • Saves changes to personalize their theme tracking

Technical Specifications

Recommended Tools and Methods:

  1. Cursor (AI-powered coding tool) for development assistance
  2. Web scraping tools for aggregating AI news from various sources
  3. Natural Language Processing (NLP) for theme categorization and summarization
  4. Machine Learning algorithms for personalization and trend analysis
  5. Web framework for building the user interface (e.g., React, Vue.js)
  6. Backend framework for server-side logic (e.g., Node.js, Django)
  7. Database for storing user data and news articles (e.g., PostgreSQL, MongoDB)
  8. Email service for sending weekly summaries (e.g., SendGrid, Mailgun)
  9. Authentication system for user accounts and privacy settings
  10. Analytics tools for tracking user interactions and generating insights

API Endpoints

  1. /api/auth/signup - POST: Create a new user account
  2. /api/auth/login - POST: Authenticate user and return token
  3. /api/news/summary - GET: Retrieve the latest weekly news summary
  4. /api/news/archive - GET: Retrieve past news summaries
  5. /api/themes - GET: Retrieve categorized AI themes
  6. /api/themes - POST: Create a custom theme category
  7. /api/themes/{id} - PUT: Update a theme category
  8. /api/themes/{id} - DELETE: Delete a theme category
  9. /api/trending - GET: Retrieve trending topics and community insights
  10. /api/profile - GET: Retrieve user profile information
  11. /api/profile - PUT: Update user profile and preferences

Database Schema

  1. Users Table:

    • id (Primary Key)
    • username
    • email
    • password_hash
    • created_at
    • last_login
    • email_preferences
    • privacy_settings

  2. News Articles Table:

    • id (Primary Key)
    • title
    • content
    • source_url
    • published_date
    • category_id (Foreign Key to Categories Table)

  3. Categories Table:

    • id (Primary Key)
    • name
    • description
    • is_auto_generated

  4. User Interactions Table:

    • id (Primary Key)
    • user_id (Foreign Key to Users Table)
    • article_id (Foreign Key to News Articles Table)
    • interaction_type (e.g., view, like, comment)
    • timestamp

  5. Themes Table:

    • id (Primary Key)
    • name
    • description
    • created_at
    • last_updated

  6. Article_Theme_Mapping Table:

    • id (Primary Key)
    • article_id (Foreign Key to News Articles Table)
    • theme_id (Foreign Key to Themes Table)

File Structure

ai-news-aggregator/ ├── frontend/ │ ├── src/ │ │ ├── components/ │ │ ├── pages/ │ │ ├── services/ │ │ ├── styles/ │ │ └── App.js │ ├── public/ │ └── package.json ├── backend/ │ ├── src/ │ │ ├── controllers/ │ │ ├── models/ │ │ ├── routes/ │ │ ├── services/ │ │ └── app.js │ ├── config/ │ └── package.json ├── scripts/ │ ├── news_scraper.py │ └── theme_analyzer.py ├── tests/ ├── docs/ └── README.md

Implementation Plan

  1. Set up development environment and version control
  2. Develop backend API and database schema
  3. Implement user authentication and account management
  4. Create news scraping and aggregation scripts
  5. Develop theme categorization and analysis algorithms
  6. Build frontend web interface for viewing summaries and managing content
  7. Implement email summary generation and delivery system
  8. Develop personalization and recommendation features
  9. Create trending topics and community insights functionality
  10. Implement user interaction tracking and analytics
  11. Conduct thorough testing and bug fixing
  12. Deploy the application to a production environment
  13. Set up monitoring and maintenance processes

Deployment Strategy

  1. Choose a cloud hosting provider (e.g., AWS, Google Cloud, or Heroku)
  2. Set up separate environments for development, staging, and production
  3. Use containerization (e.g., Docker) for consistent deployment across environments
  4. Implement CI/CD pipeline for automated testing and deployment
  5. Set up database backups and disaster recovery procedures
  6. Configure monitoring and logging tools for performance tracking
  7. Implement security measures, including SSL certificates and regular security audits
  8. Plan for scalability to handle increasing user load
  9. Establish a process for regular updates and maintenance

Design Rationale

The design decisions were made to create a user-friendly, community-driven AI news aggregation platform that caters to both individual and collective interests. The choice of a web-based interface with email summaries allows for flexibility in user engagement. The implementation of user profiles with customizable privacy settings balances personalization with data protection. The community-driven aspects, such as trending topics and shared insights, were included to enhance the value of the platform through collective intelligence. The use of AI-powered tools like Cursor for development aligns with the project's focus on AI and can potentially streamline the development process.