Discover late interaction in Apache Solr: how to implement ColBERT-style neural reranking to boost search accuracy.
Discover late interaction in Apache Solr: how to implement ColBERT-style neural reranking to boost search accuracy.
This blog summarises the main new features introduced in Apache Solr 10.0.0, focusing on Vector Search and Learning to Rank (LTR).
A comparison between Solr’s current LTR cache and a new implementation that works not only for logging features, but also for reranking.
In this blog we explores our recent contribution to Apache Solr that introduces support for SeededKnnVectorQuery.
This blog post explores binary vector quantization and the recent Solr contribution which adds support for this technique.
This blog post explores scalar vector quantization and the recent Solr contribution which adds support for this technique.
It explores an AI-powered Filter Assistant to improve User eXperience in navigating search results efficiently and effectively.
This blog post explains a workaround implemented in Solr’s CloudMLTQParser to handle fields populated via copyField.
Explore how the Apache Solr autogeneratePhraseQueries parameter works and how its default is affected by the schema version.
We are Sease, an Information Retrieval Company based in London, focused on providing R&D project guidance and implementation, Search consulting services, Training, and Search solutions using open source software like Apache Lucene/Solr, Elasticsearch, OpenSearch and Vespa.
