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From Rupinder Singh Mazara <rmaz...@masterfile.com>
Subject Re: controlled vocabulary
Date Fri, 25 Aug 2006 15:27:20 GMT
Hi Xin

   then perhaps you can change it to Field.Index.TOKENIZED, but i was 
not aware that pubmed boosts mesh terms, they broadly classify terms as 
major and minor, if you plan to use this simple system of classification 
consider adding the major terms twice to the document ?

Zhao, Xin wrote:
> Hi, Rupinder,
> My understanding is Field.Index.NO_NORMS disables  index-time boosting 
> and field length normalization at the same time. But I do need 
> index-time boosting to store the scoring of each mesh term. Have I 
> missed anything?
> Thank you very much for your help,
> Xin
>
> ----- Original Message ----- From: "Rupinder Singh Mazara" 
> <rmazara@masterfile.com>
> To: <java-user@lucene.apache.org>
> Sent: Friday, August 25, 2006 10:49 AM
> Subject: Re: controlled vocabulary
>
>
>> hi Xin
>>
>>  this is take a look at this you can add multiple fields with the 
>> name mesh
>> for ( i=0; i< meshList.size() ; i++ ){
>>    meshTerm = meshList.get(i)
>>  document.addField( new Field( "mesh", meshTerm.semanticWebConceptId, 
>> Field.Store.YES , Field.Index.NO_NORMS  );
>> }
>>
>>  when querying this index, create a analyzer that infers the text 
>> string and generates id's that correspond to the mesh term in the 
>> semantic web
>>
>>
>>
>> Zhao, Xin wrote:
>>> Hi,
>>> Thank you for your reply. I had thought about the first two 
>>> solutions before. If we apply one doc for each MeSH term, it would 
>>> be 26 docs for each item digested(we actually need the top 25 MeSH 
>>> terms generated), would it be any problem if there are too many 
>>> documents? If we apply field name like "mesh_1", "mesh_2"..., when 
>>> it comes to search, we will have to generate a loop for each single 
>>> one of the query terms( there will be more than 20-30 terms on 
>>> average, since we are using sematic web to implement concept 
>>> search), do you think it would affect the performance in a very bad 
>>> way?
>>> Regards,
>>> Xin
>>>
>>>
>>> ----- Original Message ----- From: "Dedian Guo" <gdedian@gmail.com>
>>> To: <java-user@lucene.apache.org>; "Zhao, Xin" <xzhao@jhu.edu>
>>> Sent: Thursday, August 24, 2006 4:22 PM
>>> Subject: Re: controlled library
>>>
>>>
>>>> in my solution, you can apply one doc for each mesh term, or apply 
>>>> different
>>>> keyword such as "mesh_1"...."mesh_10" for your top 10 terms...or u 
>>>> can group
>>>> your mesh terms as one string then add into a field, which requires 
>>>> a simple
>>>> string parser for the group string when you wanna read the terms...
>>>>
>>>> not sure if that works or answers your question...
>>>>
>>>> On 8/24/06, Zhao, Xin <xzhao9@jhmi.edu> wrote:
>>>>>
>>>>> Hi,
>>>>> I have a design question. Here is what we try to do for indexing:
>>>>> We designed an indexing tool to generate standard MeSH terms from 
>>>>> medical
>>>>> citations, and then use Lucene to save the terms and citations for 
>>>>> future
>>>>> search. The information we need to save are:
>>>>> a) the exact mesh terms (top 10)
>>>>> b) the score for each term
>>>>> so the codings are like
>>>>> -----------------------------------
>>>>> for the top 10 MeSH Terms
>>>>> myField=Field.Keyword("mesh", mesh.toLowerCase());
>>>>> myField.setBoost(score);
>>>>> doc.add(myFiled);
>>>>> end for
>>>>> ------------------------------------
>>>>> as you could see we generate all the terms under named field 
>>>>> "mesh". If I
>>>>> understand correctly, all the fields under the same name would
>>>>> eventually  save into one field, with all the scores be normalized 
>>>>> into
>>>>> filed boost. In this case, we wouldn't be able to save separate 
>>>>> score, so
>>>>> the information is lost. Am I correct? Is there anyway we could 
>>>>> change it? I
>>>>> understand Lucene is for keyword search, and what we try to do is 
>>>>> Controlled
>>>>> Vocabulary search, Any other tool we could use?
>>>>>
>>>>> Thank you,
>>>>> Xin
>>>>>
>>>>>
>>>>>
>>>>
>>>
>>>
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>>>
>>>
>>>
>>
>>
>>
>>
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>
>
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>
>
>




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