The transformation you talk about is called baseform reduction. Most
efficient approach is dictionary-based. Stemming is mostly restricted to
algorithmic approaches which do not cover all cases.

You could try to use or setup a new dictionary in my
elasticsearch-baseform-plugin

https://github.com/jprante/elasticsearch-analysis-baseform

Jörg


On Fri, Apr 4, 2014 at 10:35 PM, Raja Akhtar <[email protected]> wrote:

> I am fairly new to Elasticsearch and it's worked brilliantly so far.
>
> I'm stuck in this issue of singular and plural terms, and have done quite
> a bit of research on it too.... and everyone's talking "stemmers",
> "snowball", "kstem" etc...
>
> From what I understand... if I have stemmer analyzer on a term, I would
> have something like:
>
> term  =>  stem
> ----------------------------
> "knock" => "knock"
> "knocker" => "knock"
> "knocked" => "knock"
> "knocking" => "knock"
>
> Therefore, if someone searched for "knock", they would see results with
> "knocked", "knocking" etc...
> Now I can achieve that with nGrams anyway.
>
> What I'm trying to is the opposite.
>
> I want someone to be able to type "knocking"... and still find "knocker",
> "knocked" etc...
>
> In my particular use case, I want someone to be able to type "fridges" and
> still find "fridge"
>
> How do I achieve this? Can I attached some sort of a stemmer on to the
> search_analyser?
> Any help will be great.
>
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