Hey, scoring is generally one of the more complex parts of search, not because it uses math, but because everyone defines relevancy different. If you are interested, how scoring works generally, take the time to read https://lucene.apache.org/core/4_7_0/core/org/apache/lucene/search/similarities/TFIDFSimilarity.html
However, in most real applications you would want to change the scoring on different parameter of a document, for example if your are running a bidding site or a news portal, time is an important factor. This is why the function_score has been added to elasticsearch, see http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html Another interesting thing might be to score documents up, where two search terms are near to each other and so forth... The freshly released definitive guide (a not yet fully complete online book) gives a really great introduction into this, see http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/search-in-depth.html The question is, do you really want to work on such single term examples like the ladder one, to heavily affect your scores or does it make more sense to take more than full-text search into account to achieve your requirements? Also, dont mix it up with relational databases on how those queries work. Hope this helps as a start. --Alex On Thu, Mar 27, 2014 at 4:27 PM, Kelly Sauke <[email protected]> wrote: > Everyone- > > How would you solve this issue? > > I'm building a product search but I'm running into issues with > generalizing how boosting happens. In one example I search for the term > "ladder" and I get results where the terms "ladder parts" and "ladder > wheels" are higher than "step ladder" or "platform ladder". In other cases > I want a higher ranking where the search term exists at the beginning of > matched string as opposed to the end. How do I go in and boost those > specific documents but only for specific search terms? Is that possible? > > I'm using the snowball analyzer with English language. Perhaps there is a > better analyzer to use? > > Thanks for your help! > -Kelly > > > -- > You received this message because you are subscribed to the Google Groups > "elasticsearch" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > To view this discussion on the web visit https://groups.google.com/d/ > msgid/elasticsearch/53344357.4080007%40gmail.com. > For more options, visit https://groups.google.com/d/optout. > -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/CAGCwEM9vPxHBzOMXkp3Wex-Jr5xx5crGYEYpkvzeZorizTzAvw%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
