nreimers commented on issue #12342: URL: https://github.com/apache/lucene/issues/12342#issuecomment-1591318871
@msokolov The index / vector DB should return the dot product score as is. No scaling, no truncation. Using dot product is tremendously useful for embedding models, they perform in asymmetric settings where you want to map a short search query to a longer relevant document (which is the most common case in search) much better than cosine similarity or euclidean distance. But here the index should return the values as is and it should then be up to the user to truncate negative scores or to normalize these scores to pre-defined ranges. -- 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: issues-unsubscr...@lucene.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@lucene.apache.org For additional commands, e-mail: issues-h...@lucene.apache.org
