org.apache.lucene.search.similarities.LMDirichletSimilarity.java Source code

Introduction

Here is the source code for org.apache.lucene.search.similarities.LMDirichletSimilarity.java

Source

/*
 * 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 java.util.ArrayList;
import java.util.List;
import java.util.Locale;

import org.apache.lucene.search.Explanation;

/**
 * Bayesian smoothing using Dirichlet priors. From Chengxiang Zhai and John
 * Lafferty. 2001. A study of smoothing methods for language models applied to
 * Ad Hoc information retrieval. In Proceedings of the 24th annual international
 * ACM SIGIR conference on Research and development in information retrieval
 * (SIGIR '01). ACM, New York, NY, USA, 334-342.
 * <p>
 * The formula as defined the paper assigns a negative score to documents that
 * contain the term, but with fewer occurrences than predicted by the collection
 * language model. The Lucene implementation returns {@code 0} for such
 * documents.
 * </p>
 * 
 * @lucene.experimental
 */
public class LMDirichletSimilarity extends LMSimilarity {
    /** The &mu; parameter. */
    private final float mu;

    /** Instantiates the similarity with the provided &mu; parameter. */
    public LMDirichletSimilarity(CollectionModel collectionModel, float mu) {
        super(collectionModel);
        if (Float.isFinite(mu) == false || mu < 0) {
            throw new IllegalArgumentException("illegal mu value: " + mu + ", must be a non-negative finite value");
        }
        this.mu = mu;
    }

    /** Instantiates the similarity with the provided &mu; parameter. */
    public LMDirichletSimilarity(float mu) {
        if (Float.isFinite(mu) == false || mu < 0) {
            throw new IllegalArgumentException("illegal mu value: " + mu + ", must be a non-negative finite value");
        }
        this.mu = mu;
    }

    /** Instantiates the similarity with the default &mu; value of 2000. */
    public LMDirichletSimilarity(CollectionModel collectionModel) {
        this(collectionModel, 2000);
    }

    /** Instantiates the similarity with the default &mu; value of 2000. */
    public LMDirichletSimilarity() {
        this(2000);
    }

    @Override
    protected double score(BasicStats stats, double freq, double docLen) {
        double score = stats.getBoost() * (Math.log(1 + freq / (mu * ((LMStats) stats).getCollectionProbability()))
                + Math.log(mu / (docLen + mu)));
        return score > 0.0d ? score : 0.0d;
    }

    @Override
    protected void explain(List<Explanation> subs, BasicStats stats, double freq, double docLen) {
        if (stats.getBoost() != 1.0d) {
            subs.add(Explanation.match((float) stats.getBoost(), "query boost"));
        }
        double p = ((LMStats) stats).getCollectionProbability();
        Explanation explP = Explanation.match((float) p,
                "P, probability that the current term is generated by the collection");
        Explanation explFreq = Explanation.match((float) freq,
                "freq, number of occurrences of term in the document");

        subs.add(Explanation.match(mu, "mu"));
        Explanation weightExpl = Explanation.match(
                (float) Math.log(1 + freq / (mu * ((LMStats) stats).getCollectionProbability())),
                "term weight, computed as log(1 + freq /(mu * P)) from:", explFreq, explP);
        subs.add(weightExpl);
        subs.add(Explanation.match((float) Math.log(mu / (docLen + mu)),
                "document norm, computed as log(mu / (dl + mu))"));
        subs.add(Explanation.match((float) docLen, "dl, length of field"));
        super.explain(subs, stats, freq, docLen);
    }

    @Override
    protected Explanation explain(BasicStats stats, Explanation freq, double docLen) {
        List<Explanation> subs = new ArrayList<>();
        explain(subs, stats, freq.getValue().doubleValue(), docLen);

        return Explanation.match((float) score(stats, freq.getValue().doubleValue(), docLen),
                "score(" + getClass().getSimpleName() + ", freq=" + freq.getValue() + "), computed as boost * "
                        + "(term weight + document norm) from:",
                subs);
    }

    /** Returns the &mu; parameter. */
    public float getMu() {
        return mu;
    }

    @Override
    public String getName() {
        return String.format(Locale.ROOT, "Dirichlet(%f)", getMu());
    }
}