search engines

What does Deep Learning Contribute to Search

From Deep Learning for Search by Tommaso Teofili

If you’ve ever worked on designing, implementing or configuring a search engine, you’ve faced the problem of having a solution that adapts to your data; deep learning helps provide solutions to these problems which are accurately based on the data, not on fixed rules or algorithms.

Elasticsearch Percolator: search turned upside down

From Elasticsearch in Action
Elasticsearch Percolator: search turned upside down

Elasticsearch Index Scaling Out and Back In with Default Settings

From Elasticsearch in Action
Elasticsearch index scaling out and back in with default settings

Routing New Documents and Searches to the Appropriate Shards

From Elasticsearch in Action
Routing new documents and searches to the appropriate shards

Documents Going through Multiple Levels of Aggregations

From Elasticsearch in Action
Documents going through multiple levels of aggregations

Analysis Takes the Original Text and Makes Relevant Tokens Out of It

From Elasticsearch in Action
Analysis takes the original text and makes relevant tokens out of it

Solving search problems with Elasticsearch

By Radu Gheorghe, Roy Russo, and Matthew Lee Hinman, authors of Elasticsearch in Action
As a developer, you know that search engines are confronted with challenges. In this article, we’ll talk about Elasticsearch’s approach to these challenges.

Solving search problems with Elasticsearch (PDF)

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