"In vivo" spam filtering: a challenge problem for KDD

Authors:
Tom Fawcett
Affiliations:
Hewlett-Packard Laboratories, Palo Alto, CA
Venue:
ACM SIGKDD Explorations Newsletter
Year:
2003

Citing 11
Cited 28

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Abstract

Spam, also known as Unsolicited Commercial Email (UCE), is the bane of email communication. Many data mining researchers have addressed the problem of detecting spam, generally by treating it as a static text classification problem. True in vivo spam filtering has characteristics that make it a rich and challenging domain for data mining. Indeed, real-world datasets with these characteristics are typically difficult to acquire and to share. This paper demonstrates some of these characteristics and argues that researchers should pursue in vivo spam filtering as an accessible domain for investigating them.