Question about the ranking in ElasticSearch

Hallo dear all,

I have ingested a few files (more than 700.000) in an ElasticSearch Index.

The files in the index have to attachement fields where I stored fulltext
data. This field is sometimes really huge.

As I queried my index I missed one special file.

In the attachement filed "ftattach" this document has a text which has over
800 A4 pages. The word I searched for appears just one single time in the
whole text.

Maybe ElasticSearch (or Lucene) calculates that as not relevant because of
a low score.

Is there any posibility to decrement the necessary ranking-score so I can
find the missing file?

Hope you can help me.

kind regards

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Maybe it helps to index each page into a document.

Jörg

On Thu, Aug 1, 2013 at 3:23 PM, maximilian.brodhun@googlemail.com wrote:

Hallo dear all,

I have ingested a few files (more than 700.000) in an Elasticsearch Index.

The files in the index have to attachement fields where I stored fulltext
data. This field is sometimes really huge.

As I queried my index I missed one special file.

In the attachement filed "ftattach" this document has a text which has
over 800 A4 pages. The word I searched for appears just one single time in
the whole text.

Maybe Elasticsearch (or Lucene) calculates that as not relevant because of
a low score.

Is there any posibility to decrement the necessary ranking-score so I can
find the missing file?

Hope you can help me.

kind regards

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The document is a XML file which I can't divide. For other things it is
necessary that document one huge document.

There is no possibility to just decrement ranking requirements so
Elasticsearch list also results with a lower score?

Am Donnerstag, 1. August 2013 15:39:41 UTC+2 schrieb Jörg Prante:

Maybe it helps to index each page into a document.

Jörg

On Thu, Aug 1, 2013 at 3:23 PM, <maximilia...@googlemail.com <javascript:>

wrote:

Hallo dear all,

I have ingested a few files (more than 700.000) in an Elasticsearch
Index.

The files in the index have to attachement fields where I stored fulltext
data. This field is sometimes really huge.

As I queried my index I missed one special file.

In the attachement filed "ftattach" this document has a text which has
over 800 A4 pages. The word I searched for appears just one single time in
the whole text.

Maybe Elasticsearch (or Lucene) calculates that as not relevant because
of a low score.

Is there any posibility to decrement the necessary ranking-score so I can
find the missing file?

Hope you can help me.

kind regards

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"elasticsearch" group.
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email to elasticsearc...@googlegroups.com <javascript:>.
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Search is returning the document, but just not scored as high as you would
like it? If so, field length might be a problem. You can disable norms on
that field so that length normalization is not occurring.

--
Ivan

On Fri, Aug 2, 2013 at 5:34 AM, maximilian.brodhun@googlemail.com wrote:

The document is a XML file which I can't divide. For other things it is
necessary that document one huge document.

There is no possibility to just decrement ranking requirements so
Elasticsearch list also results with a lower score?

Am Donnerstag, 1. August 2013 15:39:41 UTC+2 schrieb Jörg Prante:

Maybe it helps to index each page into a document.

Jörg

On Thu, Aug 1, 2013 at 3:23 PM, <maximilia...@**googlemail.com> wrote:

Hallo dear all,

I have ingested a few files (more than 700.000) in an Elasticsearch
Index.

The files in the index have to attachement fields where I stored
fulltext data. This field is sometimes really huge.

As I queried my index I missed one special file.

In the attachement filed "ftattach" this document has a text which has
over 800 A4 pages. The word I searched for appears just one single time in
the whole text.

Maybe Elasticsearch (or Lucene) calculates that as not relevant because
of a low score.

Is there any posibility to decrement the necessary ranking-score so I
can find the missing file?

Hope you can help me.

kind regards

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Groups "elasticsearch" group.
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an email to elasticsearc...@**googlegroups.com.

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.

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