free.it.fan.pippo.baudo moderation
Zam...@free.it.fan.pippo.baudo
still produce a considerable amount of
* traffic, the data could then undergo 'secondary testing', such as the
* addition of the words "New York," to reduce the number.
You may wonder what keywords excel at picking up "resume condition" traffic.
You want the truth?
YOU CAN'T HANDLE THE TRUTH
Just kidding. That was Jack Nickelson speaking for the NSA.
Here is how it is done:
o Select all traffic.
o Exclude commonplace traffic, such as mailing lists.
example: FROM <fire...@greatcircle.com>
This is done by selecting keywords that match against the routing
information in the email header: who it came from, who it is going to.
The phone analogy is recipient and originating phone numbers.
This cuts down on "noise". "Secret Power" gave examples of this too.
o Search all traffic for a set of keywords that are found (tuned) over
time to have the best results. SOME of the ones I used:
first day
last day
resign
new job
resume
interview
drug test
It's ironic that drug testing of employees is so wide-spread that it can
be used to pick out people looking for new jobs.
o Further exclusion logic (keywords) to isolate the meaning of the
keyword 'resume' to mean job history. Also, UK people say 'CV'.
Example: do NOT allow a sentence fragment like 'resume playing'
to trigger "resume condition" inclusion.
That's how it is done.
I then sit at a terminal and page through a
summary of the results, looking for 'hits'.
That's how DICTIONARY works too.
* The Puzzle Palace, Author James Bamford, 1983 revision
*
* P496-497: You would put in a whole slew of keywords.
* You fli
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