Translating Google-style search strings to Verity

I've built a nice full-text search facility using Verity for
my application, but in these days of Google dominance, I'm afraid
few if any of my site's users are familiar with the now-peculiar
search-expression style employed by Verity. Instead, they're used
to being able to type a series of words separated by spaces and
expect it to treat spaces the way Verity treats AND expressions.
Likewise, they'll want to use quote marks around a phrase to
retrieve it in-tact. Etc, etc, etc.
I've searched for hours but can't find anything in public
where someone has done this. I suppose I could create a UDF that
carries out the task, but as I'm a master at neither tool's
expression sets, I fear it would take me days. Does anyone know of
such a UDF or tag, or at least concrete resources that might help
me in this task? Maybe just advice re the most basic conversions to
ensure my translator carries out?
Thanks in advance!

The real issues are performance and result set size.
If the query hits a large data volume, lots of I/O, lots of data transformation or processing... that could be quite slow. And way too slow to for a web user to wait for results.
If the results from the query is a 100,000 rows, what then? Streaming a 100,000 rows' results to the browser is usually not feasible. It needs to be formatted. It is very sizeable compared to what the average web page should be. Again a heavy performance impact.
Google does not search data. They search indexes (of indexes). On dedicated and clustered index servers.
When dealing with large result sets, they only plough into the first bit and give an estimate of how much there is still left.
The problem with many database web searches is that these two issues are ignored. Base tables are hit with full blown searches (lots of I/O, full table scans, massive index range scans, etc). Worse, they attempt to very accurately provide paging, stating exactly how many rows there are meeting the criteria.
This results in a massive performance impact and a web system that simply cannot scale when data volumes increase, or complex search criteria is used.
My advice is:
- make very good use of indexing, partitioning, materialised views, and so on to reduce I/O for a query to a minimum
- do not attempt to do accurate page counts (especially not when tables are dynamic)

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Hi,
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Hi,
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Translating Google-style search strings to Verity

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