@Grant
Less than a minute.  If we go with the meta-retrieval from the index, we
will have to keep the index updated down to seconds. But that may not scale
well.  Probably a hybrid approach?
I will look into classifier. thanks





Grant Ingersoll-6 wrote:
> 
> 
> On Mar 18, 2010, at 2:44 PM, caman wrote:
> 
>> 
>> 1) Took care of the first one by Transformer.
> 
> This is often also something done by a classifier that is trained to deal
> with all the statistical variations in your text.  Tools like Weka,
> Mahout, OpenNLP, etc. can be applied here.
> 
>> 2) Any input on 2 please? I need to store # of views and popularity with
>> each document and that can change pretty often. Recommended to use
>> database
>> or can this be updated to SOLr directly? My issue with DB is that with
>> every
>> SOLR search hit, will have to do DB hit to retrieve meta-data. 
> 
> Define often, please.  Less than a minute or more than a minute?
> 
>> 
>> Any input is appreciated please
>> 
>> caman wrote:
>>> 
>>> Hello all,
>>> 
>>> Please see below.any help much appreciated.
>>> 1) Extracting data out of a text field to assign a category for certain
>>> configured words. e.g. If the text is "Google does it again with
>>> Android" 
>>> and If 'Google' and 'Android' are the configured words, I want to b able
>>> to assign the article to tags 'Google' and 'Android' and 'Technical' .
>>> Can
>>> I do this with a custom filter during analysis? Similarly setting up
>>> categories for each article based on keywords in the text.
>>> 2) How about using SOLR as transactional datastore? Need to keep track
>>> of
>>> rating for each document. Would 'ExternalFileField' be good choice for
>>> this use-case?
>>> 
>>> Thanks in advance.
>>> 
>> 
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>> 
> 
> --------------------------
> Grant Ingersoll
> http://www.lucidimagination.com/
> 
> Search the Lucene ecosystem using Solr/Lucene:
> http://www.lucidimagination.com/search
> 
> 
> 

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