Lucene allows the user to customize its scoring formula by extending
org.apache.lucene.search.Similarity. The abstract
methods defined in this class match the factors of the following formula
calculating the score of query q for document d:
score(q,d) = coord(q,d) · queryNorm(q) · ∑t in q ( tf(t in d) · idf(t)2 · t.getBoost() · norm(t,d) )
| Factor | Description |
|---|---|
| tf(t ind) | Term frequency factor for the term (t) in the document (d). |
| idf(t) | Inverse document frequency of the term. |
| coord(q,d) | Score factor based on how many of the query terms are found in the specified document. |
| queryNorm(q) | Normalizing factor used to make scores between queries comparable. |
| t.getBoost() | Field boost. |
| norm(t,d) | Encapsulates a few (indexing time) boost and length factors. |
It is beyond the scope of this manual to explain this
formula in more detail. Please refer to
Similarity's Javadocs for more information.
Hibernate Search provides two ways to modify Lucene's similarity
calculation. First you can set the default similarity by specifying the
fully specified classname of your Similarity
implementation using the property
hibernate.search.similarity. The default value is
org.apache.lucene.search.DefaultSimilarity.
Additionally you can override the default similarity on class level using
the @Similarity annotation.
@Entity
@Indexed
@Similarity(impl = DummySimilarity.class)
public class Book {
...
}As an example, let's assume it is not important how often a
term appears in a document. Documents with a single occurrence of the term
should be scored the same as documents with multiple occurrences. In this
case your custom implementation of the method tf(float
freq) should return 1.0.