Class LMDirichletSimilarity
Bayesian smoothing using Dirichlet priors. From Chengxiang Zhai and John Lafferty. 2001. A study of smoothing methods for language models applied to Ad Hoc information retrieval. In Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR '01). ACM, New York, NY, USA, 334-342.
The formula as defined the paper assigns a negative score to documents that
contain the term, but with fewer occurrences than predicted by the collection
language model. The Lucene implementation returns 0 for such
documents.
@lucene.experimental
Inherited Members
Assembly: DistributedLucene.Net.dll
Syntax
public class LMDirichletSimilarity : LMSimilarityConstructors
| Name | Description |
|---|---|
| LMDirichletSimilarity() | Instantiates the similarity with the default µ value of 2000. |
| LMDirichletSimilarity(LMSimilarity.ICollectionModel) | Instantiates the similarity with the default µ value of 2000. |
| LMDirichletSimilarity(LMSimilarity.ICollectionModel, Single) | Instantiates the similarity with the provided µ parameter. |
| LMDirichletSimilarity(Single) | Instantiates the similarity with the provided µ parameter. |
Properties
| Name | Description |
|---|---|
| Mu | Returns the µ parameter. |
Methods
| Name | Description |
|---|---|
| Explain(Explanation, BasicStats, Int32, Single, Single) | |
| GetName() | |
| Score(BasicStats, Single, Single) |
