“体内”垃圾邮件过滤：数据采掘的一个挑战性问题
"In vivo" spam filtering: A challenge problem for data mining
摘要：
垃圾邮件，也被称为未经请求的商业电子邮件（UCE），是电子邮件通信的祸根。许多数据采掘研究人员已经解决了检测垃圾邮件的问题，通常将其视为静态文本分类问题。真正的体内垃圾邮件过滤具有使其成为数据采掘的丰富且具有挑战性的领域的特征。事实上，具有这些特征的真实世界数据集通常难以获取和共享。本文展示了其中的一些特点，并认为研究人员应该追求在体内垃圾邮件过滤作为一个可访问的域进行调查。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
