Hi, I'm trying to extract several similarity measures from Solr for use in a learning to rank model. Doing this mathematically involves taking the dot product of several different matrices, which is extremely fast for non-huge data sets (e.g., millions of documents and queries). However, to extract these similarity features from Solr, I have to perform a Solr query for each query, which introduces several bottlenecks. Are there more efficient means of computing these similarity measures for large numbers of queries (other than increased parallelism)?
Thanks, Michael A. Alcorn
