As we countdown to the annual Lucene/Solr Revolution conference in Las Vegas next month, we’re highlighting talks and sessions from past conferences. Today, we’re highlighting Salesforce’s Ammar Haris & Joe Zeimen’s talk, “Customizing Ranking Models in Solr to Improve Relevance for Enterprise Search”.

Solr provides a suite of built-in capabilities that offer a wide variety of relevance related parameter tuning. Index and/or query time boosts along with function queries can provide a great way to tweak various relevance related parameters to help improve the search results ranking. In the enterprise space however, given the diversity of customers and documents, there is a much greater need to be able to have more control over the ranking models and be able to run multiple custom ranking models.

This talk discusses the motivation behind creating an L2 ranker and the use of Solr Search Component for running different types of ranking models at Salesforce.

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