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Development of AI-Powered News Aggregation and Categorization Platform
  1. case
  2. Development of AI-Powered News Aggregation and Categorization Platform

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Development of AI-Powered News Aggregation and Categorization Platform

onix-systems.com
Information technology

Challenge: Information Overload and Difficulty in News Consumption

Users are overwhelmed by the sheer volume of news available, making it difficult to find relevant and interesting content. Existing news consumption methods are inefficient, leading to decreased user engagement and missed opportunities for personalized information delivery.

About the Client

A technology company specializing in developing AI-powered solutions for various industries, focusing on enhancing user experience and data analysis.

Project Goals: Enhanced News Discovery and User Engagement

  • Develop a robust news aggregation platform capable of collecting articles from diverse sources.
  • Implement accurate and efficient news categorization using AI and machine learning techniques.
  • Improve user engagement by providing personalized news recommendations based on user preferences.
  • Enable users to easily access news in their preferred languages.
  • Ensure a seamless and user-friendly experience across multiple platforms (web and mobile).

Functional Requirements

  • News Aggregation: Ability to pull news articles from various APIs and RSS feeds.
  • AI-Powered Categorization: Accurate categorization of news articles into 10+ predefined topics.
  • Language Detection: Automatic detection of the language of each news article.
  • Personalized Recommendations: Suggest news articles based on user preferences and browsing history.
  • User Authentication: Secure user identification and access control.
  • Search Functionality: Ability to search for news articles by keyword, category, and source.
  • Filtering and Sorting: Options to filter news by category, language, date, and source.
  • Webview Interface: Accessible via web browser on desktop and mobile devices.
  • Mobile App Integration: Seamless integration with existing iOS and Android mobile applications.

Preferred Technologies

Python
LSTM Models
TensorFlow
SpaCy
NLTK
Gensim
Scikit-learn
Next.js

Required Integrations

  • News APIs (e.g., NewsAPI, GNews)
  • Social Media APIs (for content discovery)
  • Client's Existing Authentication Services
  • Client's Existing Data Storage Solutions

Non-Functional Requirements

  • Scalability: The platform must be able to handle a large volume of news articles and users.
  • Performance: Fast loading times and efficient search functionality.
  • Security: Secure storage of user data and protection against unauthorized access.
  • Reliability: High availability and minimal downtime.
  • Accuracy: High accuracy in news categorization and language detection.

Expected Business Impact

This platform is expected to significantly increase user engagement within the client's app, leading to a larger and more active user base. By providing personalized and easily accessible news content, the platform will enhance user satisfaction and drive overall business growth. A projected increase in active users to 40,000+ is anticipated within the first year of implementation.

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