SimilarityDelegator

Construct a Similarity that delegates all methods to another.

Computes the normalization value for a field, given the accumulated state of term processing for this field (see FieldInvertState).

Implementations should calculate a float value based on the field state and then return that value.

Matches in longer fields are less precise, so implementations of this method usually return smaller values when state.getLength() is large, and larger values when state.getLength() is small.

Note that the return values are computed under addDocument(org.apache.lucene.document.Document) and then stored using encodeNormValue(float). Thus they have limited precision, and documents must be re-indexed if this method is altered.

For backward compatibility this method by default calls lengthNorm(String, int) passing getLength() as the second argument, and then multiplies this value by getBoost().

Computes a score factor based on the fraction of all query terms that a document contains. This value is multiplied into scores.

The presence of a large portion of the query terms indicates a better match with the query, so implementations of this method usually return larger values when the ratio between these parameters is large and smaller values when the ratio between them is small.

Computes a score factor based on a term's document frequency (the number of documents which contain the term). This value is multiplied by the tf(int) factor for each term in the query and these products are then summed to form the initial score for a document.

Terms that occur in fewer documents are better indicators of topic, so implementations of this method usually return larger values for rare terms, and smaller values for common terms.

Computes the normalization value for a query given the sum of the squared weights of each of the query terms. This value is multiplied into the weight of each query term. While the classic query normalization factor is computed as 1/sqrt(sumOfSquaredWeights), other implementations might completely ignore sumOfSquaredWeights (ie return 1).

This does not affect ranking, but the default implementation does make scores from different queries more comparable than they would be by eliminating the magnitude of the Query vector as a factor in the score.

Calculate a scoring factor based on the data in the payload. Overriding implementations are responsible for interpreting what is in the payload. Lucene makes no assumptions about what is in the byte array.

The default implementation returns 1.

Computes the amount of a sloppy phrase match, based on an edit distance. This value is summed for each sloppy phrase match in a document to form the frequency that is passed to tf(float).

A phrase match with a small edit distance to a document passage more closely matches the document, so implementations of this method usually return larger values when the edit distance is small and smaller values when it is large.

Computes a score factor based on a term or phrase's frequency in a document. This value is multiplied by the idf(int, int) factor for each term in the query and these products are then summed to form the initial score for a document.

Terms and phrases repeated in a document indicate the topic of the document, so implementations of this method usually return larger values when freq is large, and smaller values when freq is small.