The following operators can be used to better focus your queries.
( ) , AND, OR, NOT, W/#
? single char wildcard, not at start
* multi char wildcard, not at start
(Cat? OR feline) AND NOT dog?
Cat? W/5 behavior
(Cat? OR feline) AND traits
Cat AND charact*
This guide provides a more detailed description of the syntax that is supported along with examples.
This search box also supports the look-up of an IP.com Digital Signature (also referred to as Fingerprint); enter the 72-, 48-, or 32-character code to retrieve details of the associated file or submission.
Concept Search - What can I type?
For a concept search, you can enter phrases, sentences, or full paragraphs in English. For example, copy and paste the abstract of a patent application or paragraphs from an article.
Concept search eliminates the need for complex Boolean syntax to inform retrieval. Our Semantic Gist engine uses advanced cognitive semantic analysis to extract the meaning of data. This reduces the chances of missing valuable information, that may result from traditional keyword searching.
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.
English (United States)
This text was extracted from a PDF file.
100% of the total text.
Page 01 of 3
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.
Page 02 of 3
Figure 1: System learning and training steps
Page 03 of 3
Figure 2: Components and process in a preferred embodiment