Class In_expB2

  • All Implemented Interfaces:, java.lang.Cloneable, Model

    public class In_expB2
    extends WeightingModel
    This class implements the In_expB2 weighting model, namely Inverse Expected Document Frequency model with Bernoulli after-effect and normalisation 2. The logarithms are base 2. This model can be used for classic ad-hoc tasks.
    Gianni Amati, Ben He, Vassilis Plachouras
    See Also:
    Serialized Form
    • Constructor Detail

      • In_expB2

        public In_expB2()
        A default constructor. This must be followed by specifying the c value.
      • In_expB2

        public In_expB2​(double c)
        Constructs an instance of this class with the specified value for the parameter beta.
        c - the term frequency normalisation parameter value.
    • Method Detail

      • getInfo

        public final java.lang.String getInfo()
        Returns the name of the model.
        Specified by:
        getInfo in interface Model
        Specified by:
        getInfo in class WeightingModel
        the name of the model
      • score

        public final double score​(double tf,
                                  double docLength)
        This method provides the contract for implementing weighting models.
        Specified by:
        score in class WeightingModel
        tf - The term frequency in the document
        docLength - the document's length
        the score assigned to a document with the given tf and docLength, and other preset parameters