DirichletSimilarity

Namespace

Rowles.LeanCorpus.Search.Scoring

Assembly

Rowles.LeanCorpus.dll

Language-model similarity with Dirichlet (Bayesian) smoothing. Smooths the document model towards the collection model using a prior parameter μ.

Score = log((tf + μ · P(t|C)) / (|d| + μ)), where P(t|C) = collectionFrequency / totalTermsInCollection.

Default μ = 2000 (optimised for short to medium-length documents).

public sealed class DirichletSimilarity : ISimilarity

Inheritance

object

DirichletSimilarity

Implements

ISimilarity

DirichletSimilarity(float)

Initialises a new instance with the specified Dirichlet prior μ.

Instance

Gets a shared singleton instance with the default μ = 2000.

RequiresCollectionStatistics

Whether this similarity requires collection-level statistics (total term frequency and total terms in collection) for scoring.

PrecomputeFactors(int, int, float)

Precomputes factors constant for a given term across all documents.

PrecomputeLmFactors(int, int, float, long, long)

Precomputes factors including collection-level term statistics for language-model similarities. Default simply delegates to PrecomputeFactors(int, int, float) and sets CollectionProb to 0.

Score(int, int, float, int, int)

Computes the score for a single term occurrence in a document.

ScoreLmPrecomputed(float, float, float, int, int)

Scores using precomputed language-model factors. Default delegates to ScorePrecomputed(float, float, int, int), ignoring collectionProb.

ScorePrecomputed(float, float, int, int)

Scores using precomputed factors for hot-path scoring.