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  1. Return-Path: <icon-group-sender>
  2. Received: from kingfisher.CS.Arizona.EDU (kingfisher.CS.Arizona.EDU [192.12.69.239])
  3.     by baskerville.CS.Arizona.EDU (8.8.7/8.8.7) with SMTP id IAA28479
  4.     for <icon-group-addresses@baskerville.CS.Arizona.EDU>; Tue, 17 Mar 1998 08:04:06 -0700 (MST)
  5. Received: by kingfisher.CS.Arizona.EDU (5.65v4.0/1.1.8.2/08Nov94-0446PM)
  6.     id AA21124; Tue, 17 Mar 1998 08:04:05 -0700
  7. Date: Mon, 16 Mar 98 18:46:30 -0500
  8. Message-Id: <9803162346.AA0130@valinet.com>
  9. From: Paul Abrahams <abrahams@acm.org>
  10. To: icon-group@optima.CS.Arizona.EDU
  11. Subject: Re: Letter Probabilities
  12. Reply-To: abrahams@acm.org
  13. Errors-To: icon-group-errors@optima.CS.Arizona.EDU
  14. Status: RO
  15. Content-Length: 417
  16.  
  17. Using the probabilities to construct a weighted string and then
  18. selecting a random character from the string does have one unaesthetic
  19. property, in my book: the length of the string grows exponentially with
  20. the precision of the probabilities.  For that reason I'd opt for a
  21. binary search, which takes 5 probes no matter what the precision.
  22.  
  23. I wonder if there's another way of attacking this problem.
  24.  
  25. Paul Abrahams
  26.  
  27.