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>Web Feed System

Personalized Web Feed System

Development & Case Study

Project Overview

CodeAlign is developing a personalized content aggregation platform that enables users to build their own custom information feed. By leveraging web scraping, the system curates real-time updates from multiple sources based on individual user preferences. The project focuses on helping users cut through the noise of the internet by delivering relevant, high-quality information through a streamlined and responsive feed.

Problem Statement

In an age of information overload, users are constantly bombarded with irrelevant or low-quality content. Traditional newsfeeds and aggregators lack flexibility, control, and often promote sensational or algorithmically biased content. There was a clear need for a tool that empowers users to control what they see and when they see it—without compromising accuracy or user experience.

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Solution Implemented

  • Enable content selection based on keywords, topics, or URLs defined by users.

  • Allow users to add multiple data sources for a holistic yet focused feed.

  • Display curated content in a personalized dashboard or feed interface.

  • Push real-time notifications when new relevant content is available.

  • Track changes in curated data to ensure up-to-date delivery.

  • Plan future AI integration for smart content suggestions and misinformation detection.

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Visual design screenshot

Visual Design

  • The design approach centers around minimalism and clarity.

  • The feed interface uses card-style content blocks for easy scanning, with source filters and content tags integrated into the UI.

  • The notification system is unobtrusive yet immediate, styled to match both desktop and mobile interfaces.
    The color scheme is clean and modern, highlighting content without visual clutter.

Achievements

  • Successfully implemented multi-source content scraping with real-time feed update capability.

  • Developed a user-controlled feed configuration system with granular preferences.

  • Deployed a functional push notification service to alert users of new or updated content.

  • Early user tests show a 70% reduction in time spent filtering content manually.

  • Laid the groundwork for an AI-driven recommendation engine and misinformation detection module.