|
E-mail Filtering
Email filtering is the processing of email to organize it according to specified criteria. The term can apply to the intervention of human intelligence, but most often refers to the automatic processing of messages at an SMTP server, possibly applying anti-spam techniques. Filtering can be applied to incoming emails as well as to outgoing ones. Depending on the calling environment, email filtering software can reject an item at the initial SMTP connection stage or pass it through unchanged for delivery to the user's mailbox. It is also possible to redirect the message for delivery elsewhere, quarantine it for further checking, modify it or 'tag' it in any other way. Motivation Common uses for mail filters include organizing incoming email and removal of spam and computer viruses. Mailbox providers filter outgoing email to promptly react to spam surges that may result from compromised accounts. A less common use is to inspect outgoing email at some companies to ensure that emplo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Email
Electronic mail (email or e-mail) is a method of exchanging messages ("mail") between people using electronic devices. Email was thus conceived as the electronic ( digital) version of, or counterpart to, mail, at a time when "mail" meant only physical mail (hence '' e- + mail''). Email later became a ubiquitous (very widely used) communication medium, to the point that in current use, an email address is often treated as a basic and necessary part of many processes in business, commerce, government, education, entertainment, and other spheres of daily life in most countries. ''Email'' is the medium, and each message sent therewith is also called an ''email.'' The term is a mass noun. Email operates across computer networks, primarily the Internet, and also local area networks. Today's email systems are based on a store-and-forward model. Email servers accept, forward, deliver, and store messages. Neither the users nor their computers are required to be online simult ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Leak Prevention
Data loss prevention (DLP) software detects potential data breaches/data ex-filtration transmissions and prevents them by monitoring, detecting and blocking sensitive data while ''in use'' (endpoint actions), ''in motion'' (network traffic), and ''at rest'' (data storage). The terms "data loss" and "data leak" are related and are often used interchangeably.Asaf Shabtai, Yuval Elovici, Lior Rokach,A Survey of Data Leakage Detection and Prevention Solutions Springer-Verlag New York Incorporated, 2012 Data loss incidents turn into data leak incidents in cases where media containing sensitive information is lost and subsequently acquired by an unauthorized party. However, a data leak is possible without losing the data on the originating side. Other terms associated with data leakage prevention are information leak detection and prevention (ILDP), information leak prevention (ILP), content monitoring and filtering (CMF), information protection and control (IPC) and extrusion prevention ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Markovian Discrimination
Within the probability theory Markov model, Markovian discrimination in spam filtering is a method used in CRM114 and other spam filters to model the statistical behaviors of spam and nonspam more accurately than in simple Bayesian methods. A simple Bayesian model of written text contains only the dictionary of legal words and their relative probabilities. A Markovian model adds the relative transition probabilities that given one word, predict what the next word will be. It is based on the theory of Markov chains by Andrey Markov, hence the name. In essence, a Bayesian filter works on single words alone, while a Markovian filter works on phrases or entire sentences. There are two types of Markov models; the visible Markov model, and the hidden Markov model or HMM. The difference is that with a visible Markov model, the current word is considered to contain the entire state of the language model, while a hidden Markov model hides the state and presumes only that the current word ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Information Filtering
An information filtering system is a system that removes redundant or unwanted information from an information stream using (semi)automated or computerized methods prior to presentation to a human user. Its main goal is the management of the information overload and increment of the semantic signal-to-noise ratio. To do this the user's profile is compared to some reference characteristics. These characteristics may originate from the information item (the content-based approach) or the user's social environment (the collaborative filtering approach). Whereas in information transmission signal processing filters are used against syntax-disrupting noise on the bit-level, the methods employed in information filtering act on the semantic level. The range of machine methods employed builds on the same principles as those for information extraction. A notable application can be found in the field of email spam filters. Thus, it is not only the information explosion that necessitates so ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CRM114 (program)
CRM114 (full name: "The CRM114 Discriminator") is a program based upon a statistical approach for classifying data, and especially used for filtering email spam. Origin of the name The name comes from the CRM-114 Discriminator in the Stanley Kubrick movie Dr. Strangelove - a piece of radio equipment designed to filter out messages lacking a specific code-prefix. Operation While others have done statistical Bayesian spam filtering based upon the frequency of single word occurrences in email, CRM114 achieves a higher rate of spam recognition through creating hits based upon phrases up to five words in length. These phrases are used to form a Markov Random Field representing the incoming texts. With this additional contextual recognition, it is one of the more accurate spam filters available. Initial testing in 2002 by author Bill Yerazunis gave a 99.87% accuracy; Holden and TREC 2005 and 2006 [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Bayesian Spam Filtering
Naive Bayes classifiers are a popular statistical technique of e-mail filtering. They typically use bag-of-words features to identify email spam, an approach commonly used in text classification. Naive Bayes classifiers work by correlating the use of tokens (typically words, or sometimes other things), with spam and non-spam e-mails and then using Bayes' theorem to calculate a probability that an email is or is not spam. Naive Bayes spam filtering is a baseline technique for dealing with spam that can tailor itself to the email needs of individual users and give low false positive spam detection rates that are generally acceptable to users. It is one of the oldest ways of doing spam filtering, with roots in the 1990s. History Bayesian algorithms were used for email filtering as early as 1996. Although naive Bayesian filters did not become popular until later, multiple programs were released in 1998 to address the growing problem of unwanted email. The first scholarly publi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft Outlook
Microsoft Outlook is a personal information manager software system from Microsoft, available as a part of the Microsoft Office and Microsoft 365 software suites. Though primarily an email client, Outlook also includes such functions as Calendaring software, calendaring, Time management#Software applications, task managing, contact manager, contact managing, note-taking, Transaction log, journal logging and Web navigation, web browsing. And has also become a popular email client for many businesses. Individuals can use Outlook as a Software, stand-alone application; organizations can deploy it as multi-user software (through Microsoft Exchange Server or SharePoint) for such shared functions as Email box, mailboxes, Calendaring software, calendars, Shared resource, folders, data aggregation (i.e., SharePoint lists), and Appointment scheduling software, appointment scheduling. Mobile app, Apps of Outlook for Mobile operating system, mobile platforms are also offered. Web appl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Processing
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves. Challenges in natural language processing frequently involve speech recognition, natural-language understanding, and natural-language generation. History Natural language processing has its roots in the 1950s. Already in 1950, Alan Turing published an article titled "Computing Machinery and Intelligence" which proposed what is now called the Turing test as a criterion of intelligence, t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Naive Bayes Classifier
In statistics, naive Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong (naive) independence assumptions between the features (see Bayes classifier). They are among the simplest Bayesian network models, but coupled with kernel density estimation, they can achieve high accuracy levels. Naive Bayes classifiers are highly scalable, requiring a number of parameters linear in the number of variables (features/predictors) in a learning problem. Maximum-likelihood training can be done by evaluating a closed-form expression, which takes linear time, rather than by expensive iterative approximation as used for many other types of classifiers. In the statistics literature, naive Bayes models are known under a variety of names, including simple Bayes and independence Bayes. All these names reference the use of Bayes' theorem in the classifier's decision rule, but naive Bayes is not (necessarily) a Bayesian method. Introductio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Document Classification
Document classification or document categorization is a problem in library science, information science and computer science. The task is to assign a document to one or more classes or categories. This may be done "manually" (or "intellectually") or algorithmically. The intellectual classification of documents has mostly been the province of library science, while the algorithmic classification of documents is mainly in information science and computer science. The problems are overlapping, however, and there is therefore interdisciplinary research on document classification. The documents to be classified may be texts, images, music, etc. Each kind of document possesses its special classification problems. When not otherwise specified, text classification is implied. Documents may be classified according to their subjects or according to other attributes (such as document type, author, printing year etc.). In the rest of this article only subject classification is considered. T ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Procmail
procmail is an email server software component — specifically, a message delivery agent (MDA). It was one of the earliest mail filter programs. It is typically used in Unix-like mail systems, using the mbox and Maildir storage formats. procmail was first developed in 1990, by Stephen R. van den Berg. Philip Guenther took over maintainership for a number of years, but relinquished the role in 2014. The software remained unmaintained for several years, and was believed to be defunct. In 2020 May, Stephen van den Berg resumed maintenance again. The program has since seen multiple releases and bug-fixes. Uses The most common use case for procmail is filter mail into different mailboxes, based on criteria such as sender address, subject keywords, and/or mailing list address. Another use is to let procmail call an external spam filter program, such as SpamAssassin. This method can allow for spam to be filtered or deleted. The procmail developers have built a mailing lis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data-driven Programming
In computer programming, data-driven programming is a programming paradigm in which the program statements describe the data to be matched and the processing required rather than defining a sequence of steps to be taken. Standard examples of data-driven languages are the text-processing languages sed and AWK, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers. Related paradigms Data-driven programming is similar to event-driven programming, in that both are structured as pattern matching and resulting processing, and are usually implemented by a main loop, though they are typically applied to different domains. The condition/action model is also similar to aspect-oriented programming, where when a join point (condition) is reached, a pointcut (action) is executed. A similar paradigm is used in some tracing frameworks such as DTrace, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
