Hi,
Right, ok.
For an exact match boost to work, you'd have to index into another field
with a different analysis chain anyway, or am I missing something? I may
not be experienced enough in this, but I can't see a way to give the
original term higher boost. Also, would filter need to be a graph filter
for positions etc. to work properly?
I suppose it would be relatively simple to add support for protwords to
ICUFoldingFilter, but I'd be concerned of the potential inconsistency
from user's perspective if you'd require exact match for certain
characters only for some words.
--Ere
Jan Høydahl kirjoitti 26.8.2021 klo 11.39:
Hi,
Thanks for the input. We already use the filter parameter to guard æøåäö. We
could of course guard é or ô against normalization too, but thise becomes quite
broad, and much of the benefit disappears.
If the filter supported some kind of protwords-list for exceptions, we could
start assembling words that we know for sure clashes and should be excepted,
however an exact-match rank boost approach would seem more flexible.
Jan
26. aug. 2021 kl. 10:08 skrev Ere Maijala <ere.maij...@helsinki.fi>:
Hi,
For our Finnish audience we avoid folding some characters to alleviate the
problem. Along with MappingCharFilter this works pretty well. See
https://github.com/NatLibFi/finna-solr/blob/dev/vufind/biblio/conf/schema.xml#L7
for examples. Depending on your use case this could be a solution as well.
Note that the filter parameter hasn't always been there, so a recent-enough
Solr version is needed (I fail to recall the exact version).
--Ere
Jan Høydahl kirjoitti 25.8.2021 klo 16.43:
Hi,
I'm looking at using ICUFoldingFilter for a customer, to fold e.g. Genéve to
Geneve and thus get better recall.
However, for some common Norwegian words, the folding makes them clash with
super-common words so it becomes impossible to find exactly what you want.
I imagined if ICUFoldingFilter had a preserverOriginal=true option, then it could leave
the original word in the index on the same position, and an exact match for
"Genéve" would score better than the normalized one. But this filter does not
support this.
Have anyone found a workaround for this, except from duplicating all content in
different fields with different analysis and search across them with different
weights?
Jan
--
Ere Maijala
Kansalliskirjasto / The National Library of Finland
--
Ere Maijala
Kansalliskirjasto / The National Library of Finland
