A Collaborative Learning Method For Spam Filtering
Hsiu-Sen Chia, Jui-Chi Shen, Dong‐Her Shih, Chia-Shyang Lin · Research in Computing Science · 2005
Spam, also known as Unsolicited Commercial Email (UCE), is the bane of email communication. It has brought enormous cost for the companies or users that use Internet. Spam filtering has made considerable progress in recent years. The predominant approaches are data mining methods and machine learning methods. Researchers have largely concentrated on either one of the approaches since a principled unifying framework is still lacking. This paper suggests that both approaches can be combined under a collaborative learning framework. We propose a collaborative learning algorithm that parallelly uses three different machine learning methods. The resultant algorithm is simple and understandable, and offers a principled solution to combine content-based filtering and collaborative filtering. Within our algorithm, we are now able to interpret various existing techniques from a unifying point of view. Finally we demonstrate the success of the proposed collaborative filtering methods in the experiment