It looks like Meta's Vibes feed is just the start of the company's pivot toward AI slop. In an earnings call, CEO Mark Zuckerberg said that "we're going to add yet another huge corpus of content" to ...

Want to know how content is scored, ranked, and in some cases, discarded by Perplexity? Independent researcher Metehan Yesilyurt analyzed browser-level interactions with Perplexity’s infrastructure to ...

This project is an AI-powered movie recommendation system built using Python and Streamlit. It leverages the TMDB API for movie data and integrates the Google Gemini API to act as an intelligent agent ...

Download PDF Join the Discussion View in the ACM Digital Library Figure 1. An example of interaction between a Travel Agent and a user. The agent can serve as an information carrier for travel-related ...

Abstract: A recommendation system is an analytical tool designed to provide personalized suggestions to users for specific resources such as literature, films, or music, derived from a comprehensive ...

Recommender systems have become indispensable in the information age, guiding users through vast datasets and enabling personalized, contextually relevant interactions. By leveraging user and item ...

Lightweight content-based movie recommender that converts movie metadata (titles, genres, descriptions) into TF‑IDF vectors and ranks films by cosine similarity. Clean, modular Python code with ...