Spam Blocker for Outlook. Key Features

Supporting all types of mailboxes - Spam Reader can be used with all mail accounts supported by Outlook: POP3, IMAP, HTTP and Exchange.

Bayesian Spam Filter - Implemented spam blocker is based on a Bayesian algorithm that determines the probability for a particular word or phrase to be in a spam message. This probability is used to decide whether a whole message is spam or not. This approach to filtering mail is one of the most natural and thus precise and reliable. The Bayesian algorithm uses the database, which is the result of statistical analysis of more than 20,000 spam messages.

Self-Training - Apart from regular web-updates Spam Reader increases filtering accuracy by analyzing a user's personal mailbox. The results of the analysis are used to correct the database used for spam detection. This technology makes anti-spam protection more reliable and accurate for a particular user and provides most effective protection against spammers who permanently changes tactics for spam attacks.

White List - To make filtering safer, Spam Reader uses a technique called "White List". This technique guarantees that the messages from user's regular correspondents will not be blocked as spam even if their contents look like spam. White List may include names, addresses or entire domains. The list is automatically created on the first program execution by scanning a user's address book and all saved sent messages. Also, Spam Reader automatically updates White List adding the information about the recipients of outgoing messages.



Coordinated interaction with Outlook Rules - Spam Reader features a special algorithm for interaction with Microsoft Outlook Rules. This algorithm allows the user to set the order of executing Outlook Rules and Spam Reader. This option prevents chaotic movement of spam messages between Spam folder and destination folder for some Outlook Rule in case the spam messages match up with this Rule.

Mailing lists detection - Spam Reader supports automatic recognition of newsletters and different mailing lists in order to prevent accidental filtering these messages as spam. When the program detects a mailing-list letter it suggests user to add its address to Safe Recipients List. After that all messages from this list will be treated as legitimate.

Spam and Not-Spam Dictionaries - To adjust Spam Reader filtering rules to a user's personal needs it is possible to define custom Spam and Not-Spam Dictionaries. If a message contains a word or phrase from Spam Dictionary, then it is considered as Spam. Messages containing a word or phrases from Not-Spam Dictionary will be directed to Inbox without further anti-spam filtering.