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From Karl Wettin <karl.wet...@gmail.com>
Subject Re: Reverse Lucene queries
Date Fri, 23 Jul 2010 09:06:26 GMT

23 jul 2010 kl. 08.30 skrev skant@sloan.mit.edu:

> Hi all, I have an interesting problem...instead of going from a query
> to a document collection, is it possible to come up with the best fit
> query for a given document collection (results)? "Best fit" being a
> query which maximizes the hit scores of the resulting document
> collection.

It would probably be helpful if you explained what it is you attempt  
to achieve by doing this. Are you looking for MoreLikeThis?

> How should I approach this? All suggestions appreciated.


How exepensive of an operation is this allowed to be? Can you waste  
seconds, minutes, hours or days?
Are there any requirements on the precision and recall?

I would no matter what start with looking at the output from a feature  
selection algorithm fed with the complete corpus divided in the two  
classes "query factory set" and "all other documents".

The output will not tell you why the terms are important, just that  
they probably are used when deciding when to classify documents as  
part of query factory set or all other documents.

It's hard to say where to go from there.

Create a set of selected terms available in the query factory set.
Create a set of selected terms available in all other documents.
Create a set of selected terms only available in the query factory set.
Create a set of selected terms only available in all other documents.

See if there is a simple strategy based on above that produce a good  
result.

If not you might want to look in to some evolving algorithm that  
execute queries with permutations of selected features in order to  
find the best query. Or if you have the resources, simply create all  
permutation of queries.

If it works then I think all of the steps above could be optimized,  
cached or simplified in several ways to make it speedy.

See Mahout, Weka (has a good experimenter/explorer GUI), Rapidminer,  
etc for machine learning APIs.

It should not have to be too complicated to implement a gain ratio  
feature selector using IndexReader if the term vector space is  
available.


	karl


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