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From: Ian Lea <ian.lea@gmail.com>
Date: Fri, 15 Oct 2010 14:26:56 +0100
Message-ID: <AANLkTikWim7w++-b3C1irVr4_+0uxi-cD3EBBU2DnXnx@mail.gmail.com>
Subject: Re: Overriding DefaultScore
To: java-user@lucene.apache.org
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http://www.lucidimagination.com/blog/2009/08/05/getting-started-with-payloa=
ds/
sounds a good place to start.

A much simpler alternative, although without exact control, would be
to use query boosting.  There is also CustomScoreQuery - complex but
powerful.


--
Ian.


On Fri, Oct 15, 2010 at 2:19 PM, Zaharije Pasalic
<pasalic.zaharije@gmail.com> wrote:
> Can anybody explain or point me to couple of links where i can find
> more info about payloads?
>
> Thx
>
> On Fri, Oct 15, 2010 at 11:09 AM, Danil =C5=A2ORIN <torindan@gmail.com> w=
rote:
>> You could encode term score as payload while indexing, and use those
>> payloads on search time.
>>
>> On Fri, Oct 15, 2010 at 11:30, Zaharije Pasalic
>> <pasalic.zaharije@gmail.com> wrote:
>>> Hi
>>>
>>> my original problem is to index large number of documents which
>>> contains 360 integers in rage from 0-90K. Searching it's a little bit
>>> complicated - I need to find most similar documents where query data
>>> is also 360 numbers in range 0-90K. But (there is always 'but') i need
>>> to create score with some predefined weight table. Here is example:
>>>
>>> Index contains:
>>>
>>> DOC1 : 1, 3, 5
>>> DOC2 : 1, 100
>>> DOC3 : 1, 5
>>>
>>> I need to find all documents which are 'like' this:
>>>
>>> SEARCH: 1,5,100
>>>
>>> And suppose that i'm having table which says: "if value is larger than
>>> 10 wight hit as 0.5, else as 1" (in real application this is more
>>> complicated weight table).
>>>
>>> So for Query 1,5,100 i will have:
>>>
>>> DOC1: SCORE=3D2 =C2=A0 =C2=A0[1,5]
>>> DOC3: SCORE=3D2 =C2=A0 =C2=A0[1,5]
>>> DOC2: SCORE=3D1.5 [1,100 (100>10- wight 0.5]
>>>
>>> Searching is just: if hits occurs on field, increments score by 1*weigh=
t(value)
>>>
>>> My first step was to create index with one field which contains all
>>> 360 values and to remove normals from it.
>>>
>>> Now when i'm doing search like:
>>>
>>> "F:1 F:5 F:100"
>>>
>>> I'm getting results ok but score is not correct. Of course it gives me
>>> score sorted by 'number of hits' (am I right?) but score value is not
>>> calculated by increments of 1 nor i'm using wights at all.
>>>
>>> So, my question is - is this even possible with lucene and if can, can
>>> you point me into some directions (i already looked a little bit at
>>> DefaultSimilarity overriding).
>>>
>>> Thanks
>>>
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>>
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