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Topic: Bayesian spam filter

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	Better Bayesian Filtering
		Spam filtering is a subset of text classification, which is a well established field, but the first papers about Bayesian spam filtering per se seem to have been two given at the same conference in 1998, one by Pantel and Lin [2], and another by a group from Microsoft Research [3].
		Spam filtering is not just classification, because false positives are so much worse than false negatives that you should treat them as a different kind of error.
		The reason the filters caught them was that both companies in January switched to commercial email senders instead of sending the mails from their own servers, and both the headers and the bodies became much spammier.
	www.paulgraham.com /better.html (4059 words)

	Bayesian spam filtering - Wikipedia, the free encyclopedia
		Bayesian spam filtering is the process of using Bayesian statistical methods to classify documents into categories.
		Bayesian filtering was proposed by Sahami et al.
		For instance, Bayesian spam filters will typically have learned a very high spam probability for the words "Viagra" and "refinance", but a very low spam probability for words seen only in legitimate email, such as the names of friends and family members.
	en.wikipedia.org /wiki/Bayesian_filtering (860 words)

	Bayesian Spam Filter (Site not responding. Last check: )
		The bayesian spam filter research accessible since the internet was made available has increased in description.
		If you for sure long to learn more about topics related to bayesian spam filter, then you should be dedicated and spend the time essential to come across the top websites to get the news.
		The field centered around bayesian spam filter is a stimulating field and studying more about it can prove to be quite productive.
	www.useeknet.info /Spam/Spam-Filter/Bayesian-Spam-Filter.cfm (766 words)

	The Advantages of Bayesian Spam Filters
		Bayesian Spam Filters work by analyzing and calculating the probability of the contents in the email being spam, and self-building a list of characteristics of both spam and good elements in the message.
		Bayesian spam filtering technique is a great way of filtering out the spam from reaching your inbox.
		Legitimate emails you receive are different from the spam, and the Bayesian spam filter will assign a lower rate of probability of its being spam.
	www.pcmantra.com /Content/The-Advantages-of-Bayesian-Spam-Filters.htm (513 words)

	Warring On Spam through Bayesian Spam Filters
		Bayesian Spam Filters war on spam through the following methods: email is assessed on the probability of it being either spam or legitimate; it builds its own list of characteristics; keeps on updating its list, learning from its mistakes, thereby increasing its accuracy.
		Bayesian spam filtering technology gave hope of inboxes that could be spam free.
		The Bayesian spam filter can be trained by an individual user, who categorizes each email as either spam or not spam.
	www.pcmantra.com /Content/Warring-On-Spam-through-Bayesian-Spam-Filters.htm (483 words)

	Spam Reader - Bayesian Spam Filter for Microsoft Outlook
		Spam Reader — a spam filter for Microsoft Outlook® — uses the Bayesian approach to distinguish spam and non-spam messages.
		The base is used for learning the spam filter: for every word appearing in those messages the number of entries in spam messages and in non-spam ones is counted.
		So, to make filtering the most effective for a particular user it is necessary that the spam filter could learn on the message database of this user and automatically make adjustments when filtering is incorrect.
	www.spam-reader.com /bayesian-spam-filter.shtml (472 words)

	Plan for Spam FAQ
		If they wanted to send you to a url that is known to the filters, for example, they would find it hard to tune their way around that.
		Unfortunately, new addresses are not nearly as rich a source of spam as addresses that people have had for ten years, and used to register domain names, post to newsgroups, etc. Ask any old-time sysadmin.
		When you do that it's called a "naive Bayesian" algorithm and in practice it works pretty well, just as in practice (if you stay away from the edges of precision) it works pretty well to treat floating point numbers as if they were reals.
	www.paulgraham.com /spamfaq.html (1804 words)

	How the Bayesian spam filter works
		Bayesian filtering is based on the principle that most events are dependent and that the probability of an event occurring in the future can be inferred from the previous occurrences of that event.
		Before email can be filtered using this method, the user needs to generate a database with words and tokens (such as the $ sign, IP addresses and domains, and so on), collected from a sample of spam email and valid email (referred to as ‘ham’).
		This Bayesian approach to spam is highly effective - a May 2003 BBC article reported that spam detection rates of over 99.7% can be achieved with a very low number of false positives.
	support.gfi.com /manuals/en/me12/me12manual.1.13.html (788 words)

	How the Bayesian spam filter works
		Before mail can be filtered using this method, the user needs to generate a database with words and tokens (such as the $ sign, IP addresses and domains, and so on), collected from a sample of spam mail and valid mail (referred to as `ham').
		This is done by analyzing the users' outbound mail and by analyzing known spam: All the words and tokens in both pools of mail are analyzed to generate the probability that a particular word points to the mail being spam.
		On the other hand, the Bayesian filter, if tailored to your company through an initial training period, takes note of the company's valid outbound mail (and recognizes "mortgage" as being frequently used in legitimate messages), and therefore has a much better spam detection rate and a far lower false positive rate.
	support.gfi.com /manuals/en/me10/me10manual-1-12.html (773 words)

	What is Bayesian filter? - A Word Definition From the Webopedia Computer Dictionary
		Bayesian filtering is predicated on the idea that spam can be filtered out based on the probability that certain words will correctly identify a piece of e-mail as spam while other words will correctly identify a piece of e-mail as legitimate and wanted.
		Bayesian filters examine the words in a body of an e-mail, its header information and metadata, word pairs and phrases and even HTML code that can identify, for example, certain colors that can indicate a spam e-mail.
		Bayesian filters are adaptable in that the filter can train itself to identify new patterns of spam and can be adapted by the human user to adjust to the user’s specific parameters for identifying spam.
	www.webopedia.com /TERM/B/Bayesian_filter.html (612 words)

	buryspam -- A Bayesian Spam Filter
		Move legitimate and spam messages to separate directories: In order for Bayesian filtering to be effective, one must have an existing collection of legitimate e-mail (this includes messages from mailing lists and personal mailings -- both from you and to you) and also a collection of spam messages.
		If Bayesian analysis determined that the message was not spam, but the ratio of bad words to good words at the extrema is greater than this number, the message will be classified as spam.
		During filtering, this parameter is used to determine how the filter should handle duplicate words during the evaluation of the message.
	www.cs.mun.ca /~donald/buryspam (3607 words)

	spamcan - A Bayesian spam filter
		A Plan for Spam mail filtering setup, in which he employs Bayesian statistical analysis.
		It looks for the fifteen most "interesting" words in your message (those which most strongly link it to spam or to non-spam), and uses the "spam score" of those keywords as judges in a vote as to the disposition of the message.
		Remember, you have to make sure that the stuff you say is non-spam is actually not spam, and whatever you say is spam really is spam, because whatever you give it as an example will be what it looks for in the future.
	woozle.org /~neale/src/spamcan/spamcan.html (442 words)

	Bayesian spam filters
		A Bayesian spam filter is a complex algorithm used in estimating the probability or the likelihood that certain content or material detected by Google is in fact spam.
		However, it is the general feeling in the SEO community that, unfortunately, the current Bayesian spam filter implementation seems to have extreme and unpredictable consequences that were practically impossible to be aware of beforehand.
		Spam being a growing problem day by day, today’s modern search engines have no choice other than to implement better and more “intelligent” spam-filtering algorithms that can make the difference between what is considered as spam and what isn’t.
	www.rankforsales.com /bayesian-spam-filters.html (1535 words)

	filter past spam (Site not responding. Last check: )
		A bayesian spam filter is a new breed of spam filter that is based on the mathematical theorms of Thomas Bayes.
		In its simplest form, a spam filter is a mechanism for...
		The key is enlisting experts to filter spam for you, quickly and efficiently.
	spam.dotcombinat.com /filter-past-spam.htm (437 words)

	CodeProject: A Naive Bayesian Spam Filter for C#. Free source code and programming help
		This is a C# implementation of Paul Graham's Naive Bayesian Spam Filter algorithm.
		Googling up "Bayesian C#", I was amazed to find that nobody has put out a Naive Bayesian Spam Filter for C# that you can simply drop into your codebase.
		After all, mine is just a straight implementation of Paul Graham's original Naive Bayesian Spam filtering algorithm, and I don't pretend to have anything interesting to add to his analysis.
	www.codeproject.com /KB/recipes/BayesianCS.aspx (2487 words)

	Google Spam Filtering Gone Bad
		It is hypothesized that the changes are a result of the implementation of a "Bayesian spam filtering" algorithm, which is producing unintended consequences.
		Crashes from poison spam sites could still be detected, though now were much less of a concern to the typical user.
		While too complicated to fully explain here, a "Bayesian spam filter" is a method for probabilistically estimating the likelihood that material is spam.
	sethf.com /anticensorware/google/bayesian-spam.php (945 words)

	Bayesian filter: Spam blocking software: G-Lock SpamCombat
		The Bayesian filtering is a much more intelligent approach because it examines all aspects of a message, as opposed to keyword checking that classifies a mail as spam on the basis of a single word.
		The Bayesian filter is constantly self-adapting - by learning from new spam and new valid inbound mails, the Bayesian filter evolves and adapts to new spam techniques.
		The Bayesian filter also takes into account certain languages deviations or the diverse usage of certain words in different areas, even if the same language is spoken.
	www.glocksoft.com /sc/bayesian_filter.htm (702 words)

	dbacl project homepage
		Many people these days depend on Bayesian filters to protect them from the ever present email scourge that is spam.
		People are often astonished at how well statistical mail filtering works after they first try it, and it's tempting to imagine that such programs actually understand the emails being delivered, rather than merely matching patterns.
		Now chess has always been a popular gauge of intelligence that everyone can understand, so if we put all these ideas together, then the question "Can a Bayesian spam filter play chess?" seems like a fun experiment with a lot of appeal.
	dbacl.sourceforge.net /spam_chess-1.html (390 words)

	[Evolution] applying Bayesian spam filter (Site not responding. Last check: )
		specifically, bogofilter (http://www.tuxedo.org/~esr/bogofilter/) Applying it to incoming e-mail is fairly trivial via a filter, pipe the message to a shell command and dump it to a Spam folder depending on the return value.
		This way I can make the filter "learn" spam that it missed, or messages thought to be spam that are not.
		Then when I highlight the message and hit the hotkey, it executes the filter which would execute the shell command and move the message to the appropriate folder.
	lists.ximian.com /pipermail/evolution/2002-November/022876.html (157 words)

	Bayesian Filter - Spam MailBox - SmarterTools Forums (Site not responding. Last check: )
		The only way to mark as spam for the Bayesian filter is to manually mark themas spam.
		Bayesian filtering does not take into account where the mail came from.
		Most spam has a lot of the same words in it, so this filter goes based on that idea.
	forum.smartertools.com /ShowPost.aspx?PostID=9412 (275 words)

	Matador - A free junk-mail/spam Bayesian filter for Outlook 2003 with C# (Site not responding. Last check: )
		Bayesian algorithms are based on assigning a probability from the existing knowledge to any new item that comes to the filter.
		The filter is based on analyzing your own email probabilities (because everyone emails are different), so it would be good to fill both spam and no-spam corpus with your own definitions (done automatically by the add-in)...
		Larry, the filter engine is completed and integrated within outlook 2003, but the options and some whitelist options will be released on the next version (scheduled for next wednesday)...
	blogs.clearscreen.com /migs/archive/2004/09/16/400.aspx (2932 words)

	bogofilter(1): fast Bayesian spam filter - Linux man page
		In short, this is how it works: The estimates for the spam probabilities of the individual tokens are combined using the "inverse chi-square function".
		A spam message will be registered on the spamlist and a non-spam message on the goodlist.
		Prime the bogofilter databases with a spam and non-spam corpus.
	linux.die.net /man/1/bogofilter (2909 words)

	KnockOut Spam - Outlook antispam software with bayesian spam filter.
		However, it is a good idea to watch the Unsure and Spam folders closely for the first few weeks and correct it accordingly by moving messages the their proper folders as needed to increase the accuracy of KnockOut Spam.
		The filter adjustment selector allows you to select what Bayesian rank a message needs to receive to be categorized as Good, Unsure, and Spam.
		Learn from messages that are moved to different folders allows KnockOut Spam to learn from messages that may have been miscategorized that you have not dropped and dragged into their proper folders.
	www.knockoutspam.com /help.php (796 words)

	GFI adds Bayesian anti-spam filter to GFI MailEssentials for Exchange/SMTP 9
		Bayesian filters are widely acclaimed to be the best way to tackle spam because they use statistical intelligence to analyze the content of the mail.
		The GFI MailEssentials Bayesian filter can learn from spam identified by the user, as well as by downloading profiles of the latest spam from the GFI site, ensuring that it recognizes the latest spam and spamming techniques.
		This is not a database of spam signatures (a technology that is largely useless), but a database of spam that the Bayesian filter studies and adapts to.
	www.gfi.com /news/en/mes9launch.htm (803 words)

	Bayesian spam filtering - NoSpamToday! uses Bayesian filtering to stop spam before it gets to you!
		In order to avoid spam, it is therefore clear that the anti-spam measures need to be just as intelligent - and with Bayesian spam filtering, this can be accomplished.
		The basic principle behind Bayesian filters is that they calculate the likeliness of any given message being spam.
		In order for spam to be correctly identified, you first need to teach the software the difference between spam and regular messages.
	www.nospamtoday.com /bayesian-filtering.html (316 words)

	Spam \| drupal.org
		The Bayesian filter does statistical analysis on spam content, learning from spam and non-spam that it sees to determine the liklihood that new content is or is not spam.
		Or, a custom filter can be defined to increase the probability that content is spam if it matches the case insensitive regular expression /free/i.
		The spam module can also limit the total number of URLs allowed in comments and other content, as well as the number of times the same URL can be repeated in the same content.
	drupal.org /node/11104 (595 words)

	602LAN SUITE - Mail server with integrated Bayesian email spam filter control
		Spam is an ever-increasing problem and the number of spam mail is growing daily.
		The Bayesian filter will automatically analyze and rate the content of each processed message.
		The main advantage is that the filtering process is self-healing, meaning that when the content of spam mail changes, so do the abilities to filter it.
	www.software602.com /products/ls/spamfilter.html (392 words)

	What is a Bayesian filter?
		A Bayesian filter uses a branch of science, known as statistics, to help identify spam.
		This software filter creates two kinds of tables: one is for words that routinely appear in legitimate e-mail, and the other for words that appear in spam, and it assigns each word a "score."
		If you have anti spam software that uses a Bayesian filter you must take an active role in making it as effective as it can be.
	www.antispamyellowpages.com /what_is_a_bayesian_filter.html (244 words)

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