| Package | Description | 
|---|---|
| org.terrier.matching.models | 
 Provides the classes that implement various weighting models. 
 | 
| org.terrier.matching.tsms | 
 Provides the interface and classes that implement the term
score modifiers, which modify the scores assigned to documents
for a particular term. 
 | 
| org.terrier.querying | 
 Provides the interfaces and classes for the querying 
API of the Terrier platform, the controls, post processors
and filters. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
BB2
This class implements the BB2 weighting model. 
 | 
class  | 
BM25
This class implements the Okapi BM25 weighting model. 
 | 
class  | 
BM25F
A convenience subclass of PerFieldNormWeightingModel setup to
 do specifically BM25F, as described by [Zaragoza TREC-2004]. 
 | 
class  | 
DFIC
Divergence From Independence model based on Chi-square statistics  
 (i.e., standardized Chi-squared distance from independence in term frequency tf). 
 | 
class  | 
DFIZ
Divergence From Independence model based on Standardization 
 (i.e., standardized distance from independence in term frequency tf). 
 | 
class  | 
DFR_BM25
This class implements the DFR_BM25 weighting model. 
 | 
class  | 
DFRee
This class implements the DFRee weighting model. 
 | 
class  | 
DFReeKLIM
This class implements the DFReeKLIM weighting model. 
 | 
class  | 
DFRWeightingModel
This class implements a modular Divergence from Randomness weighting model. 
 | 
class  | 
DirichletLM
Bayesian smoothing with Dirichlet Prior. 
 | 
class  | 
Dl
This class implements a simple document length weighting model. 
 | 
class  | 
DLH
This class implements the DLH weighting model. 
 | 
class  | 
DLH13
This class implements the DLH13 weighting model. 
 | 
class  | 
DPH
This class implements the DPH hypergeometric weighting model. 
 | 
class  | 
Hiemstra_LM
This class implements the Hiemstra LM weighting model. 
 | 
class  | 
IFB2
This class implements the IFB2 weighting model. 
 | 
class  | 
In_expB2
This class implements the In_expB2 weighting model, namely Inverse Expected Document Frequency model with 
 Bernoulli after-effect and normalisation 2. 
 | 
class  | 
In_expC2
This class implements the In_expC2 weighting model. 
 | 
class  | 
InB2
This class implements the InB2 weighting model, namely
 Inverse Document Frequency model with Bernoulli after-effect and normalisation 2. 
 | 
class  | 
InL2
This class implements the InL2 weighting model. 
 | 
class  | 
Js_KLs
This class implements the Js_KLs weighting model, which is the product 
 of two measures: the Jefrreys' divergence with the Kullback Leibler's divergence. 
 | 
class  | 
LemurTF_IDF
This class implements the TF_IDF weighting model as it is implemented in Lemur. 
 | 
class  | 
LGD
This class implements the LGD weighting model. 
 | 
class  | 
MDL2
This class implements the MDL2 field-based weighting model. 
 | 
class  | 
ML2
This class implements the ML2 field-based weighting model. 
 | 
class  | 
PerFieldNormWeightingModel
A class for generating arbitrary per-field normalisation models. 
 | 
class  | 
PL2
This class implements the PL2 weighting model. 
 | 
class  | 
PL2F
A convenience subclass of PerFieldNormWeightingModel setup to
 do specifically PL2F. 
 | 
class  | 
SingleFieldModel
Use a normal weighting model on a pre-determine subset of the field. 
 | 
class  | 
StaticFeature
Class for query independent features loaded from file. 
 | 
class  | 
StaticScoreModifierWeightingModel
Base abstract class for query independent features loaded from file. 
 | 
class  | 
Tf
This class implements a simple Tf weighting model. 
 | 
class  | 
TF_IDF
This class implements the TF_IDF weighting model. 
 | 
class  | 
WeightingModel
This class should be extended by the classes used
 for weighting terms and documents. 
 | 
class  | 
XSqrA_M
This class implements the XSqrA_M weighting model, which computed the 
 inner product of Pearson's X^2 with the information growth computed 
 with the multinomial M. 
 | 
| Modifier and Type | Class and Description | 
|---|---|
class  | 
RequiredTermModifier
Resets the scores of documents according to whether a term is required 
 or not, and whether it appears in the retrieved documents. 
 | 
class  | 
TermInFieldModifier
Resets the scores of documents according to whether a term appears in 
 a given set of fields. 
 | 
| Modifier and Type | Method and Description | 
|---|---|
protected Model | 
Manager.getWeightingModel(Request rq)
Returns the weighting model requested by the Reqes from
 the WeightingModel factory. 
 | 
Terrier 4.0. Copyright © 2004-2014 University of Glasgow