Relevance is a critical aspect of a successful implementation of a search solution, and tuning it to get it right is essential to the success of search projects. During the Lucene/Solr Revolution session, “Solr Relevance Tuning Simplified,” Daniel Ling, Senior Architect at Findwise, will share some best-practices for working with relevance, including three uses case examples of the impact of customized relevance based on scenarios from the media industry and an intelligence agency, as well as a case of personalized relevance based on role.

In addition, during the session, a Solr relevance tuning module will be open sourced (on GitHub) and demonstrated. The module contains functionality to adjust the relevance parameters in an appealing UI with sliders and parameters, all providing immediate feedback and impact on search results displayed and re-ranked within the UI.

This intermediate level session will take place from 2:00-2:45 on Wednesday, November 6. Click here for more details.

About the Speaker:


Daniel Ling comes from Stockholm, Sweden, and has implemented 30+ search project implementations in many different industries and countries. He has been working with enterprise search since 2006, initially with FAST and recently more focused on Solr and ElasticSearch. He is currently a Senior Architect at Findwise.


More Details:

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Lucene/Solr Revolution is presented by Lucidworks, the commercial entity for Apache Lucene/Solr open source search — the future of search technology.

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