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 ...

For those weary of relentless nuisance calls, there's a simple way to tackle them so they don't bother you again, and it only takes a few clicks. These steps will only work if you own an Apple iPhone ...

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 ...

The takeaway: The new system positions YouTube among the first major online platforms to embed large-scale identity-protection capabilities directly into its content moderation tools. The feature ...

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 ...