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BasicModelD.cs
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BasicModelD.cs
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using System;
namespace Lucene.Net.Search.Similarities
{
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/// <summary>
/// Implements the approximation of the binomial model with the divergence
/// for DFR. The formula used in Lucene differs slightly from the one in the
/// original paper: to avoid underflow for small values of <c>N</c> and
/// <c>F</c>, <c>N</c> is increased by <c>1</c> and
/// <c>F</c> is always increased by <c>tfn+1</c>.
/// <para/>
/// WARNING: for terms that do not meet the expected random distribution
/// (e.g. stopwords), this model may give poor performance, such as
/// abnormally high scores for low tf values.
/// <para/>
/// @lucene.experimental
/// </summary>
public class BasicModelD : BasicModel
{
/// <summary>
/// Sole constructor: parameter-free </summary>
public BasicModelD()
{
}
public override sealed float Score(BasicStats stats, float tfn)
{
// we have to ensure phi is always < 1 for tiny TTF values, otherwise nphi can go negative,
// resulting in NaN. cleanest way is to unconditionally always add tfn to totalTermFreq
// to create a 'normalized' F.
double F = stats.TotalTermFreq + 1 + tfn;
double phi = (double)tfn / F;
double nphi = 1 - phi;
double p = 1.0 / (stats.NumberOfDocuments + 1);
double D = phi * SimilarityBase.Log2(phi / p) + nphi * SimilarityBase.Log2(nphi / (1 - p));
return (float)(D * F + 0.5 * SimilarityBase.Log2(1 + 2 * Math.PI * tfn * nphi));
}
public override string ToString()
{
return "D";
}
}
}