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.
This article discloses a method for protecting valid email in the in-box from deletion by detecting overzealous spam deletion.
English (United States)
This text was extracted from a PDF file.
This is the abbreviated version, containing approximately
51% of the total text.
Page 1 of 1
Method for Protecting Valid Email from Overzealous Spam Deletion
Unsolicited email has become a problem so large that it is threatening to destroy the value of email communication. Over the past several months, spam volume has increased dramatically. Valuable email is being drowned out by spam. Random, intermittent and casual conversations are the most at peril. Conversations between people who don't know each other well, or have forgotten that they know each other, now routinely get trashed. Most people employ spam filtering and yet still wind up deleting many emails. Valid email is being deleted along with bad because the sender did not pick a non-spam sounding subject or is someone who the recipient is not used to receiving email from. The core of this idea is to warn email users if they are about to delete an interesting email without first reading it.
A common spam filtering technique is Bayesian filtering. Bayesian filtering employees two lists (or corpuses). One list (spam corpus) contains words and phrases that are commonly associated with spam, and the other list (non-spam corpus) contains words and phrases that are commonly associated with non-spam/valid email. When an email arrives, the words of that email are screened against the spam and non-spam corpuses and a score is calculated determining how closely the email matches previously received spam. If the incoming email exceeds a user defined threshold for spam correspondence, for example 75%, the user may opt to have the email deleted or moved to a spam folder without viewing it. De...