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 with a mix of relevancy and facet count
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? -- View this message in context: http://lucene.472066.n3.nabble.com/SolrFaceting-Help-improving-suggestions-tag-tp4194814.html Sent from the Solr - User mailing list archive at Nabble.com.
