Um, before I consider improving your algorithm, if I can,  is this a
homework problem? Are you making money off this search application?

Just need to be clear about such a give me a boost question, I think.

-----Original Message-----
From: thakkar.aayush [mailto:[email protected]] 
Sent: Monday, March 23, 2015 6:41 AM
To: [email protected]
Subject: Improve suggestion tags for solr search query

Whenever a term is searched, we display the results and related tags. (We
provide tags to each post using pre defined tags library) We would like to
improve the tag suggestions to the user.

In the current implementation, related tags are shown based on facet counts
for the search. But we intend to use combination of search relevance score
(using lucene which uses vestor space model) with the search query and the
facet count both.

We tried implementing the following :

Suggesting the tags to the user on the custom score that is uses facet count
and search relevance score both. Mathematical model:

CustomScore= ((score - 1) * 0.3 + 1) * facetCount score - Actual score of
the faceted tags that lucene gives when searched against the search query.
facetCount - Facet count of the results extracted from the searches shown to
the user.
0.3 - Boost factor

Any suggestion on this approach or better ways to get better tags based on
relevancy and facet count?



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