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Automated tagging and categorization of email messages based on analytics of existing tagged messages

IP.com Disclosure Number: IPCOM000239244D
Publication Date: 2014-Oct-23
Document File: 3 page(s) / 52K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system for the automated tagging and categorization of email messages based on an analysis of what is already tagged and stored for the user.

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Automated tagging and categorization of email messages based on analytics of existing tagged messages

Email users apply tagging and archiving methods to organize and save email messages. A user can manually create automated rules, but these are strict, static rules that do not adapt or learn.

A method is needed to enable the user to more quickly categorize and move an

email from the primary inbox to an archive subfolder after reading the email.

The novel contribution is a system for the automated tagging and categorization of email messages based on an analysis of what is already tagged and stored for the user. The analysis can also assist with moving the message to a sub-mailbox. The novel system is comprised of methods for automated tagging, suggested tagging, and recommended actions based on analysis that leverage previously tagged content/activity.

The system uses analytics tools to analyze sender, recipients, subject, keywords, distribution list, and email content. It compares this data to items already tagged. It then suggests tags, which the user can auto-accept or manually apply. This is done through a new action button pre-populated with "Tag as ____" or "Move to _____",
matching similar messages.

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Figure 1: System learning and training steps

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Figure 2: Components and process in a preferred embodiment

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