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/*
* 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 org.apache.lucene.search.Explanation;
import static org.apache.lucene.search.similarities.SimilarityBase.log2;
/**
* Geometric as limiting form of the Bose-Einstein model. The formula used in Lucene differs
* slightly from the one in the original paper: {@code F} is increased by {@code 1}
* and {@code N} is increased by {@code F}.
* @lucene.experimental
*/
public class BasicModelG extends BasicModel {
/** Sole constructor: parameter-free */
public BasicModelG() {}
@Override
public final double score(BasicStats stats, double tfn, double aeTimes1pTfn) {
// just like in BE, approximation only holds true when F << N, so we use lambda = F / (N + F)
double F = stats.getTotalTermFreq() + 1;
double N = stats.getNumberOfDocuments();
double lambda = F / (N + F);
// -log(1 / (lambda + 1)) -> log(lambda + 1)
double A = log2(lambda + 1);
double B = log2((1 + lambda) / lambda);
// basic model G should return (A + B * tfn)
// which we rewrite to B * (1 + tfn) - (B - A)
// so that it can be combined with the after effect while still guaranteeing
// that the result is non-decreasing with tfn since B >= A
return (B - (B - A) / (1 + tfn)) * aeTimes1pTfn;
}
@Override
public Explanation explain(BasicStats stats, double tfn, double aeTimes1pTfn) {
double F = stats.getTotalTermFreq() + 1;
double N = stats.getNumberOfDocuments();
double lambda = F / (N + F);
Explanation explLambda = Explanation.match((float) lambda,
"lambda, computed as F / (N + F) from:",
Explanation.match((float) F,
"F, total number of occurrences of term across all docs + 1"),
Explanation.match((float) N,
"N, total number of documents with field"));
return Explanation.match(
(float) (score(stats, tfn, aeTimes1pTfn) * (1 + tfn) / aeTimes1pTfn),
getClass().getSimpleName() + ", computed as " +
"log2(lambda + 1) + tfn * log2((1 + lambda) / lambda) from:",
Explanation.match((float) tfn, "tfn, normalized term frequency"),
explLambda);
}
@Override
public String toString() {
return "G";
}
}