Abstract: Text messaging (SMS) remains widely used due to its simplicity and accessibility. However, its popularity has led to a rise in spam messages, including ads, scams, and phishing links.

This project implements a context-aware spam detection system using Python. Unlike naive filters, it does not assume unknown senders are scammers. Decisions are made using behavior-based scoring and ...

Ailsa Ostovitz has been accused of using AI on three assignments in two different classes this school year. "It's mentally exhausting because it's like I know this is my work," says Ostovitz, 17. "I ...

They look, move and even smell like the kind of furry Everglades marsh rabbit a Burmese python would love to eat. But these bunnies are robots meant to lure the giant invasive snakes out of their ...

This project implements a machine learning model to classify SMS messages as "spam" or "ham" (not spam) using Decision Trees and TF-IDF vectorization. CS_Project_II/ ├── dataset/ │ └── spam.csv # SMS ...

Abstract: We propose a new spam detection technique using the text clustering based on vector space model. Our method computes disjoint clusters automatically using a spherical k-means algorithm for ...