An evaluation of Naive Bayesian anti-spam filtering

Can a Simple Spam Filter Stop Junk Mail? New Tests Reveal Surprises

Researchers tried a very simple, word-based filter to spot unwanted email, and they shared the test data so others can try it too.
They checked how the filter changes when you track more or less words, use more example mail to learn from, turn words into their base form, or ignore common words — and those choices did matter.
The filter usually catches a lot of junk, but sometimes it will blocks real messages, so it isn't perfect.
The team found that with more examples the filter gets better, but you still need extra guard rails before trusting it alone.
That means adding a human check, or backup rules, to keep important mail safe.
Overall this shows a simple method can help cut spam, yet it also shows why we need careful checks, shared public data for testing, and attention to how many words the system learns.
If you want less junk mail, this is a promising start — but also a reminder that safety nets are still needed for real use.

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An evaluation of Naive Bayesian anti-spam filtering

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