Many resources are needed to download a project. Please understand that we have to compensate our server costs. Thank you in advance. Project price only 1 $
You can buy this project and download/modify it how often you want.
/*
* SPDX-License-Identifier: Apache-2.0
*
* The OpenSearch Contributors require contributions made to
* this file be licensed under the Apache-2.0 license or a
* compatible open source license.
*/
/*
* Licensed to Elasticsearch under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch 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.
*/
/*
* Modifications Copyright OpenSearch Contributors. See
* GitHub history for details.
*/
package org.opensearch.search.suggest.phrase;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.Terms;
import org.apache.lucene.util.BytesRef;
import org.opensearch.search.suggest.phrase.DirectCandidateGenerator.Candidate;
import java.io.IOException;
//TODO public for tests
public final class LinearInterpolatingScorer extends WordScorer {
private final double unigramLambda;
private final double bigramLambda;
private final double trigramLambda;
public LinearInterpolatingScorer(
IndexReader reader,
Terms terms,
String field,
double realWordLikelihood,
BytesRef separator,
double trigramLambda,
double bigramLambda,
double unigramLambda
) throws IOException {
super(reader, terms, field, realWordLikelihood, separator);
double sum = unigramLambda + bigramLambda + trigramLambda;
this.unigramLambda = unigramLambda / sum;
this.bigramLambda = bigramLambda / sum;
this.trigramLambda = trigramLambda / sum;
}
double trigramLambda() {
return this.trigramLambda;
}
double bigramLambda() {
return this.bigramLambda;
}
double unigramLambda() {
return this.unigramLambda;
}
@Override
protected double scoreBigram(Candidate word, Candidate w_1) throws IOException {
join(separator, spare, w_1.term, word.term);
final long count = frequency(spare.get());
if (count < 1) {
return unigramLambda * scoreUnigram(word);
}
return bigramLambda * (count / (0.5d + w_1.termStats.totalTermFreq)) + unigramLambda * scoreUnigram(word);
}
@Override
protected double scoreTrigram(Candidate w, Candidate w_1, Candidate w_2) throws IOException {
join(separator, spare, w.term, w_1.term, w_2.term);
final long count = frequency(spare.get());
if (count < 1) {
return scoreBigram(w, w_1);
}
join(separator, spare, w.term, w_1.term);
return trigramLambda * (count / (1.d + frequency(spare.get()))) + scoreBigram(w, w_1);
}
}