Bayesian inference has also gained prominence in E-mail spam-fighting, and in non-spam-related areas such as customer affinity engines (or, commercial recommendation engines).

Techniques such as Bayesian networks or neural networks use highly expressive models, which try to produce a non-biased classifier in order to "describe" a corpus of documents.

In "A Plan for Spam" (see Resources later in this article), Graham suggested building Bayesian probability models of spam and non-spam words.