A Memory-Based Approach to Anti-Spam Filtering for Mailing Lists

This paper presents an extensive empirical evaluation of memory-based learning in the context of anti-spam filtering, a novel cost-sensitive application of text categorization that attempts to identify automatically unsolicited commercial messages that flood mailboxes. Focusing on anti-spam filtering for mailing lists, a thorough investigation of the effectiveness of a memory-based anti-spam filter is performed using a publicly available corpus. The investigation includes different attribute and distance-weighting schemes, and studies on the effect of the neighborhood size, the size of the attribute set, and the size of the training corpus. Three different cost scenarios are identified, and suitable cost-sensitive evaluation functions are employed. We conclude that memory-based anti-spam filtering for mailing lists is practically feasible, especially when combined with additional safety nets. Compared to a previously tested Naive Bayes filter, the memory-based filter performs on average better, particularly when the misclassification cost for non-spam messages is high.     

Code and moral values in cyberspace

This essay is a critique of LarryLessig's book, Code and other Laws ofCyberspace (Basic Books, 1999). Itsummarizes Lessig's theory of the fourmodalities of regulation in cyberspace: code,law, markets, and norms. It applies thistheory to the topics of privacy and speech,illustrating how code can undermine basicrights or liberties. The review raisesquestions about the role of ethics in thismodel, and it argues that ethical principlesmust be given a privileged position in anytheory that purports to deal with the shapingof behavior in cyberspace. Finally, itproposes a philosophy of ethicalself-regulation instead of an over-reliance ongovernment policy to deal with certainimproprieties and negative externalities thattend to disrupt the Net.