Year: 2025
Type: article
Abstract: This project focuses on developing anintelligent content recommendation system thatanalyzes user behavior across social mediaplatforms to deliver personalized, timely contentsuggestions. Utilizing machine learning, naturallanguage processing, and data analysis, the systemovercomes cold start challenges to ensure accuraterecommendations for new users and content.The framework has three core components: datacollection, analysis, and recommendation. Userliked and saved content from platforms likeYouTube and Reddit are grouped using K-Meansclustering, revealing key user interest themes.Temporal analytics track user interactions overtime, dynamically adjusting recommendations toalign with peak engagement periods.
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409646607