HI Srijan Thanks for replying.
I am using the BERT open source model to generate vectors. Are you aware of any minSimilary parameter threshold in knn parser ? I am working with an ecommerce dataset. So I am getting the same non relevant results and the same score if I am using any invalid search token which is not present in my index. I want to apply some kind of minimum similarity threshold so I can throw out the outliers and can get very nearest documents only. On Fri, 26 Jan 2024 at 17:05, Srijan <shree...@gmail.com> wrote: > I have been testing dense vector search on Solr and it's been working great > for me so far. Mine is an image search use case using OpenAI's CLIP model > but the configurations are pretty much the same as yours. What embedding > model are you using? And can you share a portion of the actual query? > > On Fri, Jan 26, 2024 at 6:16 AM kumar gaurav <kg2...@gmail.com> wrote: > > > HI Everyone > > > > I am using vector search in Solr 9.4. I am using cosine similarity with > knn > > parser. > > > > Same as the documentation > > > > > https://solr.apache.org/guide/solr/latest/query-guide/dense-vector-search.html > > > > Schema > > <fieldType name="knn_vector" class="solr.DenseVectorField" > > vectorDimension="768" similarityFunction="cosine"/> > > <field name="vector" type="knn_vector" indexed="true" stored="true"/> > > > > Query > > q={!knn f=vector topK=10}[1.0, 2.0, 3.0, 4.0] > > > > The problem is it always returns docs even if it's not relevant. Even if > I > > am using the xyz keyword, knn parser is returning the documents which is > > useless. I want to control the similarity of documents. I need highly > > similar documents only. Does Solr have any parameter in the knn parser > > which controls the similarity threshold ? > > > > *How can I control the minimum Similarity threshold with knn parser ?* > > > > Please help. Thanks in advance. > > > > > > -- > > Thanks & Regards > > Kumar Gaurav > > >
