Currently (using nmslib) while searching for any vector, number of results returned are always the same which are more than the mentioned k(returning from each shard/segment)
In case of incorrect or vector not at all related to the data indexed, the behaviour remains the same. Whereas, the expected would be to return no results.
Can we have a field to accept minimum similarity score to return only results having score more than the minimum similarity score, just like the one provided in ElasticSearch
Or a range, as in how close the scores of the results being returned should be to the best matched result, so as to return less results.