Package org.terrier.matching.models.basicmodel
Provides the interface and the classes for implementing the basic models for randomness in the DFR framework. The implemented classes can be used by specifying the class name in /etc/trec.models, or in property trec.model. For instance, adding a line DFRWeightingModel(P,L,2) in file /etc/trec.models tells the systems to use the PL2 model to run retrieval. P stands for class P in this package, L stands for class L in package org.terrier.matching.basicmodel, and "2" stands for class 2 in package org.terrier.matching.models.normalisation.

Class Summary Class Description B This class implements the B basic model for randomness.BasicModel This class provides a contract for implementing the basic models for randomness in the DFR framework, for use with the DFRWeightingModel class.BM This class implements the BM weighting model, which generates the original weight given by the BM25 formula, without frequency normalisation and query term weighting.Br This class implements the Bernoulli model of randomnessDFR_BM This class implements the DFR BM weighting model, which is an approximation of BM25 in the DFR framework.IF This class implements the IF basic model for randomness.In This class implements the In basic model for randomness.In_exp This class implements the In_exp basic model for randomness.P This class implements the P basic model for randomness.PL This class implements the PL weighting model.