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