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The project enhances a blogging platform with dynamic wishlists, advanced filters, real-time notifications, personalized recommendations, and interactive data visualization to boost user engagement and customization.

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Sakibft/snapScript

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Getting Started

First, run the Project :

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

name => SnapScript

Server site => https://github.com/Sakibft/snapScript-Server

live => https://p-register-and-login.web.app

five feature about my project

1.Dynamic Wishlist Integration: The website includes a dynamic wishlist feature where users can curate a personalized collection of blogs they find interesting. This adds a layer of interactivity and customization to the user experience, allowing them to save and revisit their favorite content easily.

2.Advanced Filtering Options: Goes beyond basic filtering by implementing advanced filtering options for blog listings. Users can filter blogs not only by category but also by various attributes like author, date published, or popularity, providing a tailored browsing experience.

3.Real-time Notifications: Implements real-time notifications to keep users informed about important events such as new comments on their blogs, updates to wishlisted items, or interactions with their profile. This enhances user engagement and encourages ongoing participation.

4.Personalized Recommendations: Utilizes machine learning algorithms or collaborative filtering techniques to offer personalized blog recommendations to users based on their browsing history, wishlist items, and interactions with the platform. This feature enhances user engagement and retention by delivering relevant content tailored to individual preferences.

5.Interactive Data Visualization: Integrates interactive data visualization components to present insights and trends related to blog content, user activity, or community engagement. This feature enhances the website's analytical capabilities, providing users and administrators with valuable insights into content performance and user behavior.

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The project enhances a blogging platform with dynamic wishlists, advanced filters, real-time notifications, personalized recommendations, and interactive data visualization to boost user engagement and customization.

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