Hello,
I'm just thinking about a solution for a type ahead
functionality
that shall suggest terms that the user can search for, and
that
displays how many docs are "behind" that search
(like google suggest).
When I use facet.prefix and facet.field=text, where text is
my catchall
field (and default field for searching), then only
lowercased words are
suggested, not orgininal ones. And I want to have it
independent from
the users input - it should not matter if the user enters
"fo" or "Fo",
I always want to have "Foo" suggested if this
words exists in my docs.
Is that possible?
AFAICS the limitation of this approach is, that it is
limited to single
words. E.g. when the user enters "foo ba", then he
would not get
"Foo Bar" as a suggestion (asuming that my
catchall field contains
tokenized terms).
What do you think of this: Asuming I have my own
RequestHandler,
I would split the users input to get the last word, and use
everything
but this last word as query, to limit the resulting docs (my
default
operator is AND). Afterwards I search for terms starting
with the last
word and do standard faceting stuff (calculate number of
docs for each
term).
Are there other/better approaches/solutions for type ahead
functionality
that you would recommend?
Btw: my docs contain products with the main fields name,
cat, type,
tags, brand, color - these are used for searching (copied
into the text
field).
Thanx in advance,
cheers,
Martin
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