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All the Perl that's Practical to Extract and Report

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  • To make it easier to jump to a specific presentation, I have created a timetable. It was missing from the original web site. Enjoy these highly interesting talks.

    Oliver Schmelzle, in Webcast Timetable for Spam Conference Sessions [schmelzle.net], provided the following timetable for the webcasts found at spamconference.org [spamconference.org]:

    Session 1

    0:00:30, Teodor Zlatanov, spam.el Maintainer, "Gnus vs. Spam"
    0:10:00, Bill Yerazunis, MERL, "Sparse Binary Polynomial Hash Message Filtering and The CRM114 Discriminator"
    0:32:30, Ja

  • No additional content here. Just wanted to thank you for an excellent report.
  • One thing worth pointing out is that the testing for CRM114 isn't very well done - the figures are merely real time figures for his personal email. As all well and good as that is, the other project's test data was based on split training/validation corpuses in lab conditions. And that produces different results.

    So everyone seems pretty happy with the CRM114 results, most of the other Bayesian projects are getting equivalent results. That plus CRM114's slowness (16 times slower than every other bayesian pr
  • but were immediately sued by email greeting card company Blue Mountain because their messages were being inaccurately categorized as spam.

    You would think something like this would be configurable as an exception anyway. I delete'em as soon as I get them. My mother-in-law send these things, and when she asks "did you get my card?", I say "oh sure I did"...

    I'm not opening them until there's some possibility that one of 'em is a job offer...

  • The material above was originally posted as a comment on Slashdot, before being pasted into journal entries on Slashdot and use.perl.org. Each version of the writeup has attracted comments & emails, for which I thank you. A couple of corrections have come up, and I don't want the eventual archived versions of this not to reflect those contributions (hello, future Google spelunkers!), so here's a general cross-linked addendum:
    --


    --
    DO NOT LEAVE IT IS NOT REAL.

  • Spam is an abuse of a public-writable area of your attention. It appears visually as billboards, unwanted email, and junk snail mail; audially as phone salespeople; and in full video as TV adverts.

    Individualist solutions such as spam filtering, whether email spam or visual spam [wearcam.org], obviously have limits. It puts the onus on each and every person to do the filtering, and doesn't prevent all the effort that went into creating and distributing the spam. As the people at the conference observed, all these sma