Ella for Spam Control
v1.5.6.0Ella for Spam Control organizes your Inbox and keeps it free of spam! Works with Microsoft Outlook 2000/02/03 and Outlook Express 6 is the first Smart Inbox Assistant(tm), which learns by example how...
Description
Ella for Spam Control is the first Smart Inbox Assistant which learns by example how to personally organize and automate the processing of email messages from within the Outlook or Outlook Express Inbox. By using a Wizard and integrated training toolbar, users simply provide Ella for Spam Control a few examples of messages to keep in their Inbox, and messages to move to "Later Reading" and "Spam" review folders.
Ella quickly learns the user-defined profiles and automatically places all new messages in the appropriate folders. The user can easily define new personal classifications for processing actions, converting these two classes into, for example, "Engineering Matters" and "Personal Correspondence".
Ella's adaptive learning engine is built on a high-performance associative memory technology that observes user examples, then creates, updates, and maintains a message classification model unique to each individual. Over 100 attributes of the user's example messages are analyzed and learned by Ella in order to create the profile for the user-defined message categories.
As the user's class definitions or preferences change, Ella adapts in response to user actions as new messages are moved, continuously refining the model of user's email sorting behaviors.
Ella quickly learns the user-defined profiles and automatically places all new messages in the appropriate folders. The user can easily define new personal classifications for processing actions, converting these two classes into, for example, "Engineering Matters" and "Personal Correspondence".
Ella's adaptive learning engine is built on a high-performance associative memory technology that observes user examples, then creates, updates, and maintains a message classification model unique to each individual. Over 100 attributes of the user's example messages are analyzed and learned by Ella in order to create the profile for the user-defined message categories.
As the user's class definitions or preferences change, Ella adapts in response to user actions as new messages are moved, continuously refining the model of user's email sorting behaviors.
