Chapter 7. Flexible Scoring
We will take a deep dive into Lucene's scoring methodology and explore the available options in customization. Here is a list of topics we will cover in this chapter:
- Overriding similarity
- Implementing the BM25 model
- Implementing the language model
- Implementing the divergence from randomness model
- Implementing the information-based model
Introduction
Scoring is fundamental to Lucene's search capability and accuracy. Normally, you don't see scores in search results, but it's there to help sort results by relevancy. Knowing how scoring works, its boundary will help you make informed decisions in your application design.
The goal of scoring is to objectively calculate weights to rank already matched results. The contents that ...
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