id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_ftxkkedfivdpdbnwya6qnvm66m	Clotilde Lopes	Symbiotic filtering for spam email detection	2011	20	.pdf	application/pdf	7757	1116	79	Symbiotic filtering for spam email detection that aggregates distinct local filters from several users to improve the overall performance of spam detection. Unsolicited bulk email, widely known as spam, has become a serious problem for network administrators and for Internet users in general. These class of algorithms use message features (e.g. word frequencies) for statistically discriminating email into (e.g. email users) interested on personalized filtering (e.g. spam detection). with a local CBF filter (i.e. Naive Bayes); iii) the spam detection performance not take into account the effect spamming botnets, where a large number machines are controlled for malicious messaging (Ramachandran and Feamster, on sharing of email filters among collaborating users. c = s or c = ¬s messages of Du. In (Nelson et al., 2008), it has been shown that local spam filters are vulnerable messages are ham, a robust filter should present low spam probabilities, near	./cache/work_ftxkkedfivdpdbnwya6qnvm66m.pdf	./txt/work_ftxkkedfivdpdbnwya6qnvm66m.txt