Free Spam Software
Spam blocker services
Free Spam Software Online retailer Amazon.com has begun offering
a free copy of iHateSpam from Sunbelt Software, a Windows system
administration tools provider.
The iHateSpam product is designed to reduce the amount of spam that a PC
user receives. It runs as part of the user's e-mail program and can be
used with Microsoft Outlook and Outlook Express running on a Windows
system.
Consumers are required to purchase iHateSpam and then send in a
qualifying rebate form to receive their payment back. Shipping costs
still apply. A new anti-spam software product has been launched at
digiportal.com which aims to remember which e-mails the recipient
regards as spam and which are to be kept.
ChoiceMail gives the user the option of flagging an e-mail when it is
first received as junk mail. Any subsequent messages received from the
same e-mail address will be prevented from entering the inbox. All
e-mails from first time senders will be held by ChoiceMail which then
asks the sender to go to a web site and input their name, e-mail address
and purpose for the e-mail. The form is then forwarded to the intended
recipient who chooses if they want to receive the e-mail.
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spam
The Goals of spam
The goal of spam
is to determine the intrinsic grouping in a set of unlabeled data. But
how to decide what constitutes a good spam? It can be shown that
there is no absolute “best” criterion which would be independent of the
final aim of the spam. Consequently, it is the user which must
supply this criterion, in such a way that the result of the spam
will suit their needs.
For instance, we could be interested in finding representatives for
homogeneous groups (data reduction), in finding “natural
clusters” and describe their unknown properties (“natural” data
types), in finding useful and suitable groupings (“useful” data
classes) or in finding unusual data objects (outlier detection).
For the latest information about
The Goals of spam
Who uses spam?
Many different types of organizations use
spam as a vital
part of the work. A sampling of these include:
-
Marketing:
finding groups of customers with similar behavior given a large
database of customer data containing their properties and past
buying records;
-
Biology:
classification of plants and animals given their features;
-
Libraries:
book ordering;
-
Insurance:
identifying groups of motor insurance policy holders with a high
average claim cost; identifying frauds;
-
City-planning:
identifying groups of houses according to their house type,
value and geographical location;
-
Earthquake
studies: spam observed earthquake epicenters to
identify dangerous zones;
-
WWW:
document classification; spam weblog data to discover
groups of similar access patterns.
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Free Spam Software
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