That's exactly what we advocate for in our Solr work. We call in "Test Driven Relevancy". We work closely with content experts to help build collaboration around search quality. (disclaimer, yes we build a product around this) but the advice still stands regardless.
http://www.opensourceconnections.com/2013/10/14/what-is-test-driven-search-relevancy/ Cheers -Doug Turnbull Search Relevancy Expert OpenSource Connections On Sun, Oct 20, 2013 at 4:21 PM, Furkan KAMACI <furkankam...@gmail.com>wrote: > Let's assume that you have keywords to search and different configurations > for indexing. A/B testing is one of techniques that you can use as like > Erick mentioned. > > If you want to have an automated comparison and do not have a oracle for > A/B testing there is another way. If you have an ideal result list you can > compare the similarity of your different configuration results and that > ideal result list. > > The "ideal result list" can be created by an expert just for one time. If > you are developing a search engine you can search same keywords at that one > of search engines and you can use that results as ideal result list to > measure your result lists' similarities. > > Kendall's tau is one of the methods to use for such kind of situations. If > you do not have any document duplication at your index (without any other > versions) I suggest to use tau a. > > If you explain your system and if you explain what is good for you or what > is ideal for you I can explain you more. > > Thanks; > Furkan KAMACI > > > 2013/10/18 Erick Erickson <erickerick...@gmail.com> > > > bq: How do you compare the quality of your > > search result in order to decide which schema is better? > > > > Well, that's actually a hard problem. There's the > > various TREC data, but that's a generic solution and most > > every individual application of this generic thing called > > "search" has its own version of "good" results. > > > > Note that scores are NOT comparable across different > > queries even in the same data set, so don't go down that > > path. > > > > I'd fire the question back at you, "Can you define what > > good (or better) results are in such a way that you can > > program an evaluation?" Often the answer is "no"... > > > > One common technique is to have knowledgable users > > do what's called A/B testing. You fire the query at two > > separate Solr instances and display the results side-by-side, > > and the user says "A is more relevant", or "B is more > > relevant". Kind of like an eye doctor. In sophisticated A/B > > testing, the program randomly changes which side the > > results go, so you remove "sidedness" bias. > > > > > > FWIW, > > Erick > > > > > > On Thu, Oct 17, 2013 at 11:28 AM, Alvaro Cabrerizo <topor...@gmail.com > > >wrote: > > > > > Hi, > > > > > > Imagine the next situation. You have a corpus of documents and a list > of > > > queries extracted from production environment. The corpus haven't been > > > manually annotated with relvant/non relevant tags for every query. Then > > you > > > configure various solr instances changing the schema (adding synonyms, > > > stopwords...). After indexing, you prepare and execute the test over > > > different schema configurations. How do you compare the quality of > your > > > search result in order to decide which schema is better? > > > > > > Regards. > > > > > > -- Doug Turnbull Search & Big Data Architect OpenSource Connections <http://o19s.com>
