Hi Ivan,
Thanks for the reply. We tried using norms.enabled property and it is
working fine. But what we have observed is this attribute works only on
string types. In our application we are indexing the word (.doc,.docx) and
pdf documents and performing test based search from document content. When
we define the norm.enabled for attachments types, normalization is not
working and size of document is being considered while calculating the
score.
Please suggest how do resolve this issue for attachment types.
Code to create the index for attachment types
---
XContentBuilder map = XContentFactory.jsonBuilder().startObject()
.startObject(idxType)
.startObject("properties")
.startObject("file")
.field("type", "attachement")
.field("norms.enabled", false)
.startObject("fields")
.startObject("refid")
.field("store", "yes")
.endObject()
.startObject("name")
.field("store", "yes")
.endObject()
.startObject("itexp")
.field("store", "yes")
.endObject()
.startObject("totalexp")
.field("store", "yes")
.endObject()
.endObject()
.endObject()
.endObject()
.endObject();
---
Hiro
On Monday, 27 January 2014 23:50:41 UTC+5:30, Ivan Brusic wrote:
>
> For the third rule, you can omit index norms for a field which will
> prevent length normalization. See [1]. The option is either
> called omit_norms or norms.enabled depending on your version.
>
> For the second rule, it is slightly more complicated. You can define your
> own custom similarity [2] that dictates how the TF, IDF and norms are used.
> You simply extends Lucene's DefaultSimilarity (of TDIDFSimilarity) and at
> it to elasticsearch's classpath.
>
> [1]
> http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/mapping-core-types.html#string
> [2]
> http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/index-modules-similarity.html
>
> --
> Ivan
>
>
> On Sun, Jan 26, 2014 at 11:12 PM, Hiro Gangwani
> <[email protected]<javascript:>
> > wrote:
>
>> Dear Team,
>>
>> I have been looking at search algorithm being used in elastic search and
>> found following set of rules which are applied while calculating the score
>> (Boolean Model)
>>
>>
>> - more occurrences in the document are preferred
>> - terms rarer in the corpus are preferred
>> - shorter documents are more heavily weighted
>> - other functions used to adjust score, boosts, etc.
>>
>> In my application we are doing text based search across set of word
>> documents. We would like to assign the higher scroe to documents having
>> more occurances and show at the top irrespective of size of document.
>> Primarily our application is recruitment system where is search is based
>> upon skill sets. So our business team wants to show the resumes having more
>> occurrences of search key words at top irrespective of size and rare terms.
>> Is there any mechanism to ignore second and third rules as listed below
>> and calculate the score based upon More occurrences condition only. We are
>> executing search operations using Java API. Please let me know is it
>> possible to achieve the same and if yes how?
>>
>> Thanks in advance for suggesting solution.
>>
>> Hiro
>>
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