The completion suggester needs n! input combinations?

Elastic Stack Elasticsearch
3

we will likely add other suggesters that solve the infix problem. In a lot
of cases this suggester solves problems very efficiently and I don't think
we should advertise to use combinatorial inputs since they require
different handling on the algorithmic side. There is stuff in the pipeline
that helps here but I don't think we can just throw shingles against it and
it will work. I experimented with it but it can quickly explode which is
another thing we need to take care of. I agree we need to make the
interface better and for freetext this one will not work at this point but
I don't think this is it's purpose.

simon

On Friday, November 29, 2013 7:49:42 PM UTC+1, Karussell wrote:

Someone an idea about this?

This is probably not such a big problem with languages having spaces as
separator. Because you can easily split by space and feed some of the
combinations. But how should I make sure completion is done properly with
the other languages like chinese? Why not use a shingle token filter?

Regards,
Peter.

On Thursday, November 28, 2013 2:23:14 PM UTC+1, Karussell wrote:

Hi there,

the completion API looks really nice! There is nearly all I need like
payloads, weighting etc

But assume the example with the hotels [1]. How would you solve the
problem that the user can do the input in every possible combination
'Mercure Hotel Munich', 'Mercure Munich', 'Munich Mercure', ... ? Should I
specify 321 input values? What if my input is an address which could
consist of 6 terms (country, county, town/village, district, zipcode,
street) plus POI information which can easily lead to over 1000
combinations per entry!? Should I better use prefix query or nEdgeGram?
Another possibility would be the facet workaround [2] but this is not nice
as I need to include a payload value.

Also highlighting and (geo) filtering is currently not supported, right?

Regards,
Peter.

[1]
Elasticsearch Platform — Find real-time answers at scale | Elastic

[2]

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