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  Optimization:

  The length and uniqueness of the strings that are passed to hs_Set() are
  extremely important to the performance of HiPer-SEEK; the more uncommon
  the string, the better the performance. The .HSX index tracks text
  signatures.  The more unique signatures a particular string has, the
  easier it is for HiPer-SEEK to identify it. For example, a string like
  'tested' is made up of very common and frequently occurring characters
  and character groups. In most cases, it is more difficult (slower) for
  HiPer-SEEK to search for 'tested' than it is for it to find a string like
  'zxcvbnm' because 'tested' will produce more aliases than will 'zxcvbnm'.
  Users of HiPer-SEEK systems should always be encouraged to supply as much
  as they can for the search string.  Even additional partial words can
  sometimes make a big difference in search speeds.

  An exception to the more is better rule of HiPer-SEEK search strings is
  the case of repeated strings. Once a string has been read and the text
  signatures calculated, the addition of that same string again has no
  effect on an .HSX index search. This is true for both adding records to
  the index and passing search strings to be searched for. For example, if
  a text record contains the same word more than once, the signatures for
  that word would only be registered in the index key one time. Likewise,
  if a search string contains a repeated string, record numbers of all
  index records containing signatures for that string will be returned by
  hs_Next(). In other words, no performance improvement is realized by
  specifying a search string more than once.

  Another factor influencing the overall performance of an HiPer-SEEK
  system is the nature of the text contained in the text records. A data
  set made up of a very small vocabulary will offer HiPer-SEEK a small set
  of signatures by which to distinguish one record form another. This will
  result in more time spent verifying aliases. Conversely, a data set
  offering a large variety of signatures will allow HiPer-SEEK to perform
  closer to its theoretical best.

  HiPer-SEEK was designed to provide rapid text searches of dynamic data
  under a wide range of situations. It was specifically built to allow
  rapid additions to and updates of the index file and require small index
  files.  These facts make it less well suited to searching very large
  amounts of static data.  An example of this type of data would be in a
  CD-ROM application. Here the data will never be updated, disk space
  (index file size) is not of great concern and slow disk access speed
  makes the verification processing time even more critical.

  As you can see from the above discussion, HiPer-SEEK is a versatile and
  flexible system.  Tuning an HiPer-SEEK application can be as much art as
  science. You are encouraged to test and experiment in the early stages of
  application development.