hossman commented on code in PR #2523: URL: https://github.com/apache/solr/pull/2523#discussion_r1644774281
########## solr/solr-ref-guide/modules/query-guide/pages/dense-vector-search.adoc: ########## @@ -237,14 +237,12 @@ client.add(Arrays.asList(d1, d2)); -- == Query Time -This is the Apache Solr query approach designed to support dense vector search: -=== knn Query Parser -The `knn` k-nearest neighbors query parser allows to find the k-nearest documents to the target vector according to indexed dense vectors in the given field. The set of documents can be Pre-Filtered to reduce the number of vector distance calculations that must be computed, and ensure the best `topK` are returned. +Apache Solr provides two query parsers that work with dense vector fields, that each support differnet ways of matching documents based on vector similarity: The `knn` query parser, and the `vecSim` query parser. -The score for a retrieved document is the approximate distance to the target vector(defined by the similarityFunction configured at indexing time). +Both parsers return scores for retrieved documents that is the approximate distance to the target vector (defined by the similarityFunction configured at indexing time) and both support "Pre-Filtering" the document graph to reduce the number of candidate vectors evaluated (with out needing to compute their vector similarity distances). Review Comment: Hmmm... I think the existing wording is more grammatically correct? ... your change implies that both of the parsers return a _single_ score for _all_ of the documents? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
