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).
We explore the Combined Query Feature using Reciprocal Rank Fusion in Apache Solr with a hands-on approach.
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.
In this blog we explores an early termination strategy designed to make approximate k-NN search faster in Apache Solr.
In this blog post, we provide a comprehensive overview of the features based on large language models (LLM) currently supported by OpenSearch.
In this blog post, we examine the ColBERT paper, which adapts deep learning models, in particular, BERT, for efficient retrieval.
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.
