[Spambayes-checkins] spambayes/Outlook2000/docs welcome.html, 1.5,
1.6
Tony Meyer
anadelonbrin at users.sourceforge.net
Fri Sep 19 04:24:12 EDT 2003
Update of /cvsroot/spambayes/spambayes/Outlook2000/docs
In directory sc8-pr-cvs1:/tmp/cvs-serv16508/Outlook2000/docs
Modified Files:
welcome.html
Log Message:
Tidy up the welcome doc a bit (mostly internally, hardly any external change).
Index: welcome.html
===================================================================
RCS file: /cvsroot/spambayes/spambayes/Outlook2000/docs/welcome.html,v
retrieving revision 1.5
retrieving revision 1.6
diff -C2 -d -r1.5 -r1.6
*** welcome.html 10 Sep 2003 07:38:51 -0000 1.5
--- welcome.html 19 Sep 2003 08:24:10 -0000 1.6
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*** 12,17 ****
<td width="380"><img src="images/sblogo.jpg" title="" alt="Logo"
style="width: 380px; height: 77px;"></td>
! <!-- use background instead of styles to avoid mozilla bug 167262 --> <td
! background="images/span.jpg"> </td>
<td width="78"><img src="images/python.jpg"
style="width: 78px; height: 77px;"></td>
--- 12,17 ----
<td width="380"><img src="images/sblogo.jpg" title="" alt="Logo"
style="width: 380px; height: 77px;"></td>
! <!-- use background instead of styles to avoid mozilla bug 167262 -->
! <td background="images/span.jpg"> </td>
<td width="78"><img src="images/python.jpg"
style="width: 78px; height: 77px;"></td>
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*** 19,38 ****
</tbody>
</table>
! <h1>Welcome to SpamBayes <br>
! </h1>
<p>SpamBayes is an Outlook plugin that provides a spam filter based on
statistical analysis of
! your personal mail. Unlike many other spam detection systems,
SpamBayes
actually learns what you consider spam, and continually adapts as both
your regular email and spam patterns change.</p>
<p>When you first start Outlook after SpamBayes has been installed, the
! SpamBayes Installation Wizard will appear. This Wizard will guide
you through the configuration process and allow you to quickly have
! SpamBayes filtering your mail. This document contains additional
information which will help make SpamBayes effective from the first
time you use it.</p>
<p>Please remember that this is free software; please be patient, and
! note that there are plenty of things to improve. There are ways
you can help, even if you aren't a programmer - you could help with
this documentation, or <a
--- 19,37 ----
</tbody>
</table>
! <h1>Welcome to SpamBayes</h1>
<p>SpamBayes is an Outlook plugin that provides a spam filter based on
statistical analysis of
! your personal mail. Unlike many other spam detection systems,
SpamBayes
actually learns what you consider spam, and continually adapts as both
your regular email and spam patterns change.</p>
<p>When you first start Outlook after SpamBayes has been installed, the
! SpamBayes Installation Wizard will appear. This Wizard will guide
you through the configuration process and allow you to quickly have
! SpamBayes filtering your mail. This document contains additional
information which will help make SpamBayes effective from the first
time you use it.</p>
<p>Please remember that this is free software; please be patient, and
! note that there are plenty of things to improve. There are ways
you can help, even if you aren't a programmer - you could help with
this documentation, or <a
***************
*** 40,44 ****
any number of other ways - please see the <a
href="http://www.spambayes.org">main project
! page</a> for information. The list of <a
href="http://www.spambayes.org/faq.html">Frequently Asked Questions</a>
may also answer some of yours.</p>
--- 39,43 ----
any number of other ways - please see the <a
href="http://www.spambayes.org">main project
! page</a> for information. The list of <a
href="http://www.spambayes.org/faq.html">Frequently Asked Questions</a>
may also answer some of yours.</p>
***************
*** 49,67 ****
rules, so anything you consider spam will be treated as spam by this
system, even if it does not conform to the traditional definitions of
! spam. This means that SpamBayes requires <span
style="font-style: italic;">training </span>before it will be
! effective. There are two ways that this training can be done:<br>
<ul>
! <li>Allow SpamBayes to learn as it goes. Initially, SpamBayes
will consider all mail items <span style="font-style: italic;">unsure</span>,
and each item will be used to
! train. In this scenario, SpamBayes will take some time to become
! effective. It will rarely make mistakes, but will continue to be
unsure about items until the training information grows.<br>
</li>
<li>Pre-sorting mail into two folders; one containing only examples
! of good messages, and another containing only examples of spam.
SpamBayes will then process all these messages gathering the clues it
! uses to filter mail.. Depending on how many messages you train
on, SpamBayes will be immediately effective at correctly classifying
your mail.</li>
--- 48,66 ----
rules, so anything you consider spam will be treated as spam by this
system, even if it does not conform to the traditional definitions of
! spam. This means that SpamBayes requires <span
style="font-style: italic;">training </span>before it will be
! effective. There are two ways that this training can be done:<br>
<ul>
! <li>Allow SpamBayes to learn as it goes. Initially, SpamBayes
will consider all mail items <span style="font-style: italic;">unsure</span>,
and each item will be used to
! train. In this scenario, SpamBayes will take some time to become
! effective. It will rarely make mistakes, but will continue to be
unsure about items until the training information grows.<br>
</li>
<li>Pre-sorting mail into two folders; one containing only examples
! of good messages, and another containing only examples of spam.
SpamBayes will then process all these messages gathering the clues it
! uses to filter mail. Depending on how many messages you train
on, SpamBayes will be immediately effective at correctly classifying
your mail.</li>
***************
*** 70,76 ****
<p>It is important to note that even when SpamBayes has little training
information, it rarely gets things wrong - the worst it generally does
! is to classify a message as <span style="font-style: italic;">unsure</span>.
However, as mentioned, the more training information SpamBayes has, the
! less it is unsure about new messages. See using the plugin below
for more information.</p>
<h3>Using the Plugin</h3>
--- 69,75 ----
<p>It is important to note that even when SpamBayes has little training
information, it rarely gets things wrong - the worst it generally does
! is to classify a message as <span style="font-style: italic;">unsure</span>.
However, as mentioned, the more training information SpamBayes has, the
! less it is unsure about new messages. See using the plugin below
for more information.</p>
<h3>Using the Plugin</h3>
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*** 80,84 ****
<tr>
<td style="vertical-align: top;">This section describes how the
! plugin operates once it is configured.
You can access the SpamBayes features from the SpamBayes toolbar (shown
to the right), but
--- 79,83 ----
<tr>
<td style="vertical-align: top;">This section describes how the
! plugin operates once it is configured.
You can access the SpamBayes features from the SpamBayes toolbar (shown
to the right), but
***************
*** 88,92 ****
<td style="vertical-align: top;"><img
src="images/manager-select.jpg" title="" alt="SpamBayes Toolbar"
! style="width: 354px; height: 138px;"><br>
</td>
</tr>
--- 87,91 ----
<td style="vertical-align: top;"><img
src="images/manager-select.jpg" title="" alt="SpamBayes Toolbar"
! style="width: 354px; height: 138px;"><br/>
</td>
</tr>
***************
*** 95,105 ****
<br>
<p>As messages arrive, they are given a <span
! style="font-style: italic;">spam score</span>. This score is
the measure of how "spammy" the system has decided a mail is, with 100%
being certain spam, and 0% meaning the message is certainly not
! spam. The SpamBayes addin uses these scores to classify mail into
one of three categories -
<span style="font-style: italic;">certain spam</span>, <span
! style="font-style: italic;">unsure</span>, and good messages.
Good messages are often
known in the anti-spam community as <span style="font-style: italic;">ham</span>.</p>
--- 94,104 ----
<br>
<p>As messages arrive, they are given a <span
! style="font-style: italic;">spam score</span>. This score is
the measure of how "spammy" the system has decided a mail is, with 100%
being certain spam, and 0% meaning the message is certainly not
! spam. The SpamBayes addin uses these scores to classify mail into
one of three categories -
<span style="font-style: italic;">certain spam</span>, <span
! style="font-style: italic;">unsure</span>, and good messages.
Good messages are often
known in the anti-spam community as <span style="font-style: italic;">ham</span>.</p>
***************
*** 107,111 ****
they
will remain in your inbox, or be filtered normally by Outlook's builtin
! rules. Mail that is classified as either <span
style="font-style: italic;">unsure</span> or <span
style="font-style: italic;">certain spam</span>
--- 106,110 ----
they
will remain in your inbox, or be filtered normally by Outlook's builtin
! rules. Mail that is classified as either <span
style="font-style: italic;">unsure</span> or <span
style="font-style: italic;">certain spam</span>
***************
*** 114,131 ****
style="font-style: italic;">spam score</span> to your Outlook folder
views - but you can <a href="../about.html#Field">do it
! manually by following these instructions</a>.<br>
</p>
There are three ways in which the system can get things wrong:
<ul>
! <li>A spam stays in your inbox. This is known as a <span
! style="font-style: italic;">false negative</span>. In this case
you can either drag the message to the Spam folder or click on the <span
style="font-style: italic;">Delete as Spam</span> button on the
Outlook
! toolbar. In both cases, the message will be trained as spam and
will be moved to the spam folder.</li>
! <li>Any message is moved to the unsure folder. In this case,
the system is simply unsure about the message, and moves it to the
! possible spam folder for human review. All unsure messages should
be manually classified; good messages can either be dragged back to the
inbox, or have the <span style="font-style: italic;">Recover from Spam</span>
--- 113,130 ----
style="font-style: italic;">spam score</span> to your Outlook folder
views - but you can <a href="../about.html#Field">do it
! manually by following these instructions</a>.<br/>
</p>
There are three ways in which the system can get things wrong:
<ul>
! <li>A spam stays in your inbox. This is known as a <span
! style="font-style: italic;">false negative</span>. In this case
you can either drag the message to the Spam folder or click on the <span
style="font-style: italic;">Delete as Spam</span> button on the
Outlook
! toolbar. In both cases, the message will be trained as spam and
will be moved to the spam folder.</li>
! <li>Any message is moved to the unsure folder. In this case,
the system is simply unsure about the message, and moves it to the
! possible spam folder for human review. All unsure messages should
be manually classified; good messages can either be dragged back to the
inbox, or have the <span style="font-style: italic;">Recover from Spam</span>
***************
*** 134,155 ****
Spam folder or have the <span style="font-style: italic;">Delete as
Spam</span>
! toobar button (shown above) clicked. In all cases, the system
will
automatically
be trained appropriately.</li>
<li>A wanted (ham) message is moved to the Spam folder. This is known
! as a <span style="font-style: italic;">false positive</span>.<span
! style="font-style: italic;"></span><span style="font-style: italic;"></span> In
this case you can either drag the message back to the folder from which
it came (generally the inbox), or click on the <span
! style="font-style: italic;">Recover from Spam</span> button. In
both cases the message will be trained as good, and moved back to the
original folder.</li>
</ul>
Note that in all cases, as you take corrective action on the mail, the
! system is also trained. This makes it less likely that another
! similar mail will be incorrectly classified in the future.<br>
! <br>
! <br>
</body>
</html>
--- 133,153 ----
Spam folder or have the <span style="font-style: italic;">Delete as
Spam</span>
! toobar button (shown above) clicked. In all cases, the system
will
automatically
be trained appropriately.</li>
<li>A wanted (ham) message is moved to the Spam folder. This is known
! as a <span style="font-style: italic;">false positive</span>. In
this case you can either drag the message back to the folder from which
it came (generally the inbox), or click on the <span
! style="font-style: italic;">Recover from Spam</span> button. In
both cases the message will be trained as good, and moved back to the
original folder.</li>
</ul>
Note that in all cases, as you take corrective action on the mail, the
! system is also trained. This makes it less likely that another
! similar mail will be incorrectly classified in the future.<br/>
! <br/>
! <br/>
</body>
</html>
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