
OpenSearch Neural Search Tutorial: Hybrid Search
The new implementation of hybrid search (from OpenSearch 2.10), allows for the combination and normalization of query relevance scores.

The new implementation of hybrid search (from OpenSearch 2.10), allows for the combination and normalization of query relevance scores.

It explores the OpenSearch k-NN Plugin, which offers 3 different approaches for retrieving the k-nearest neighbors from a vector index.

This blog post explains all the steps required to implement Text Embedding and Vector Search directly in Elasticsearch in a very simple way.

In this blog post, we show in practice how you can use Elasticsearch to run a full end-to-end neural search.

In this blog post, we show in practice how you use Apache Solr to index and search vectors and then run a full end-to-end neural search.

This blog post explores the new OpenSearch neural search plugin, given a detailed description of it through our end-to-end experience.

In this final part of the Entity Search with Graph Embeddings serie we see evaluation measures and results.

Entity Search: how to build virtual documents leveraging on graph embeddings. How to exploit entity embeddings and clustering.
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.
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