Checks if a search conducted for @search_term should match
@potential_hit.
This function calls g_str_tokenize_and_fold() on both
@search_term and @potential_hit. ASCII alternates are never taken
for @search_term but will be taken for @potential_hit according to
the value of @accept_alternates.
A hit occurs when each folded token in @search_term is a prefix of a
folded token from @potential_hit.
Depending on how you're performing the search, it will typically be
faster to call g_str_tokenize_and_fold() on each string in
your corpus and build an index on the returned folded tokens, then
call g_str_tokenize_and_fold() on the search term and
perform lookups into that index.
As some examples, searching for ‘fred’ would match the potential hit
‘Smith, Fred’ and also ‘Frédéric’. Searching for ‘Fréd’ would match
‘Frédéric’ but not ‘Frederic’ (due to the one-directional nature of
accent matching). Searching ‘fo’ would match ‘Foo’ and ‘Bar Foo
Baz’, but not ‘SFO’ (because no word has ‘fo’ as a prefix).
Checks if a search conducted for @search_term should match @potential_hit.
This function calls g_str_tokenize_and_fold() on both @search_term and @potential_hit. ASCII alternates are never taken for @search_term but will be taken for @potential_hit according to the value of @accept_alternates.
A hit occurs when each folded token in @search_term is a prefix of a folded token from @potential_hit.
Depending on how you're performing the search, it will typically be faster to call g_str_tokenize_and_fold() on each string in your corpus and build an index on the returned folded tokens, then call g_str_tokenize_and_fold() on the search term and perform lookups into that index.
As some examples, searching for ‘fred’ would match the potential hit ‘Smith, Fred’ and also ‘Frédéric’. Searching for ‘Fréd’ would match ‘Frédéric’ but not ‘Frederic’ (due to the one-directional nature of accent matching). Searching ‘fo’ would match ‘Foo’ and ‘Bar Foo Baz’, but not ‘SFO’ (because no word has ‘fo’ as a prefix).