Learning To Rank – Ultimate Solr Guide

With the Learning To Rank (or LTR for short) contrib module you can configure and run machine learned ranking models in Solr. The module also supports feature extraction inside Solr. The only thing you need to do outside Solr is train your own ranking model. Learning to Rank Concepts Re-Ranking Re-Ranking allows you to run a simple query for…

Query Re-Ranking – Ultimate Solr Guide

Query Re-Ranking allows you to run a simple query (A) for matching documents and then re-rank the top N documents using the scores from a more complex query (B). Since the more costly ranking from query B is only applied to the top N documents, it will have less impact on performance then just using the complex…

The Extended DisMax (eDismax) Query Parser – Ultimate Solr Guide

The Extended DisMax (eDisMax) query parser is an improved version of the DisMax query parser. In addition to supporting all the DisMax query parser parameters, Extended Dismax: supports Solr’s standard query parser syntax such as (non-exhaustive list): boolean operators such as AND (+, &&), OR (||), NOT (-). optionally treats lowercase “and” and “or” as “AND” and “OR”…

The DisMax Query Parser – Ultimate Solr Guide

The DisMax query parser is designed to process simple phrases (without complex syntax) entered by users and to search for individual terms across several fields using different weighting (boosts) based on the significance of each field. Additional options enable users to influence the score based on rules specific to each use case (independent of user…

The Standard Query Parser – Ultimate Solr Guide

Solr’s default Query Parser is also known as the “lucene” parser. The key advantage of the standard query parser is that it supports a robust and fairly intuitive syntax allowing you to create a variety of structured queries. The largest disadvantage is that it’s very intolerant of syntax errors, as compared with something like the DisMax query…