Are these documents classified already? Sounds like it would be much faster to suppress documents with the same tags as your target tags.
On Fri, Apr 20, 2012 at 4:16 PM, Darren Govoni <dar...@ontrenet.com> wrote: > You could run the MLT for the document in question, then gather all > those doc id's in the MLT results and negate those in a subsequent > query. Not sure how robust that would work with very large result sets, > but something to try. > > Another approach would be to gather the "interesting terms" from the > document in question and then negate those terms in subsequent queries. > Perhaps with many negated terms, Solr will rank the results based on > most negated terms above less negated terms, simulating a ranked "less > like" effect. > > On Fri, 2012-04-20 at 15:38 -0700, Charlie Maroto wrote: >> Hi all, >> >> Is there a way to implement the opposite to MoreLikeThis (LessLikeThis, I >> guess :). The requirement we have is to remove all documents with content >> like that of a given document id or a text provided by the end-user. In >> the current index implementation (not using Solr), the user can narrow >> results by indicating what document(s) are not relevant to him and then >> request to remove from the search results any document whose content is >> like that of the selected document(s) >> >> Our index has close to 100 million documents and they cover multiple topics >> that are not related to one another. So, a search for some broad terms may >> retrieve documents about engineering, agriculture, communications, etc. As >> the user is trying to discover the relevant documents, he may select an >> agriculture-related document to exclude it and those documents like it from >> the results set; same w/ engineering-like content, etc. until most of the >> documents are about communications. >> >> Of course, some exclusions may actually remove relevant content but those >> filters can be removed to go back to the previous set of results. >> >> Any ideas from similar implementations or suggestions are welcomed! >> Thanks, >> Carlos > > -- Lance Norskog goks...@gmail.com
