Optimising Search Relevance Using Querqy

Optimising Search Relevance Using Querqy (Rene Kriegler, OpenSource Connections)

Elastic Berlin Meetup @ Camunda 28/09/2022
Increasingly, applications use open source technologies such as Solr and Elasticsearch to implement search. However, compared to commercial search software, there often is a feature gap in the search management capabilities. While commercial solutions normally provide convenient ways to configure search relevance rules and settings, (such as moving documents which contain a certain, query-dependent term to the top/bottom of the search result list; query-dependent filters, and query-time synonyms), in open source solutions these features are either completely missing or, under certain conditions, have scoring and recall problems.

In this talk, Rene gives an introduction to Querqy, an open source library for search query preprocessing. Querqy was started in 2014 when migrating an e-commerce search platform to Solr, specifically to provide convenient ways to configure search relevance rules and settings. It has been available for Elasticsearch since 2019. Rene also introduces Querqy as a general query rewriting framework which allows to plug in further rewriters - for example, for handling decompounding or implementing custom query rewriters.

[rajaguntupalli]

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