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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