I agree with Itamar. It sounds like you do have a list of colors and brands
(tagging), so you can add a boost value as a payload to the relevant terms.
You can use these payloads with a function score script or a custom
similarity. Not an easy solution. If you can maintain a mapping of values
in Elasticsearch (via a plugin), you can bypass the payload and lookup the
terms yourself.  Once again, not easy.

http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/analysis-delimited-payload-tokenfilter.html

-- 
Ivan


On Tue, Jun 3, 2014 at 3:00 AM, Itamar Syn-Hershko <ita...@code972.com>
wrote:

> Depending on your corpus, this should happen automatically. That's what
> TF/IDF is about.
>
> What you can do further is use NLP methods to tag those items in search
> and indexing. Look up POS tagging and entity extraction.
>
> --
>
> Itamar Syn-Hershko
> http://code972.com | @synhershko <https://twitter.com/synhershko>
> Freelance Developer & Consultant
> Author of RavenDB in Action <http://manning.com/synhershko/>
>
>
> On Tue, Jun 3, 2014 at 12:22 PM, Rotem Haber <haber.ro...@gmail.com>
> wrote:
>
>> hi,
>> Is there a search in elasticsearch that support the behavior that when a
>> user enter a string to search, the ES recognize words as important words in
>> search.
>> for example: the user enter the string NEXUS COVER FOR EVERY DAY USE SILK
>> SOFT BLUE, and I want that the brand(NEXUS) and color(BLUE) will be more
>> dominant in search, and I have a list of all the colors and all the brand
>> that exist.
>>
>> is it possible? and if yes, how do I implement that?
>>
>> thank you!
>>
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