/*
* 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.
*/
package org.apache.lucene.search.similarities;
import static org.apache.lucene.search.similarities.SimilarityBase.log2;
/**
* 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 {@code N} and
* {@code F}, {@code N} is increased by {@code 1} and
* {@code F} is always increased by {@code tfn+1}.
* <p>
* WARNING: for terms that do not meet the expected random distribution
* (e.g. stopwords), this model may give poor performance, such as
* abnormally high or NaN scores for low tf values.
* @lucene.experimental
*/
public class BasicModelD extends BasicModel {
/** Sole constructor: parameter-free */
public BasicModelD() {}
@Override
public final 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.getTotalTermFreq() + 1 + tfn;
double phi = (double)tfn / F;
double nphi = 1 - phi;
double p = 1.0 / (stats.getNumberOfDocuments() + 1);
double D = phi * log2(phi / p) + nphi * log2(nphi / (1 - p));
return (float)(D * F + 0.5 * log2(1 + 2 * Math.PI * tfn * nphi));
}
@Override
public String toString() {
return "D";
}
}