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* 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.
*/
package org.elasticsearch.search.suggest.phrase;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.Terms;
import org.apache.lucene.util.BytesRef;
import org.elasticsearch.common.ParseField;
import org.elasticsearch.common.ParsingException;
import org.elasticsearch.common.io.stream.StreamInput;
import org.elasticsearch.common.io.stream.StreamOutput;
import org.elasticsearch.common.xcontent.XContentBuilder;
import org.elasticsearch.common.xcontent.XContentParser;
import org.elasticsearch.common.xcontent.XContentParser.Token;
import org.elasticsearch.search.suggest.phrase.WordScorer.WordScorerFactory;
import java.io.IOException;
import java.util.Objects;
/**
* Linear interpolation smoothing model.
* <p>
* See <a
* href="http://en.wikipedia.org/wiki/N-gram#Smoothing_techniques">N-Gram
* Smoothing</a> for details.
* </p>
*/
public final class LinearInterpolation extends SmoothingModel {
public static final String NAME = "linear";
static final ParseField PARSE_FIELD = new ParseField(NAME);
private static final ParseField TRIGRAM_FIELD = new ParseField("trigram_lambda");
private static final ParseField BIGRAM_FIELD = new ParseField("bigram_lambda");
private static final ParseField UNIGRAM_FIELD = new ParseField("unigram_lambda");
private final double trigramLambda;
private final double bigramLambda;
private final double unigramLambda;
/**
* Creates a linear interpolation smoothing model.
*
* Note: the lambdas must sum up to one.
*
* @param trigramLambda
* the trigram lambda
* @param bigramLambda
* the bigram lambda
* @param unigramLambda
* the unigram lambda
*/
public LinearInterpolation(double trigramLambda, double bigramLambda, double unigramLambda) {
double sum = trigramLambda + bigramLambda + unigramLambda;
if (Math.abs(sum - 1.0) > 0.001) {
throw new IllegalArgumentException("linear smoothing lambdas must sum to 1");
}
this.trigramLambda = trigramLambda;
this.bigramLambda = bigramLambda;
this.unigramLambda = unigramLambda;
}
/**
* Read from a stream.
*/
public LinearInterpolation(StreamInput in) throws IOException {
trigramLambda = in.readDouble();
bigramLambda = in.readDouble();
unigramLambda = in.readDouble();
}
@Override
public void writeTo(StreamOutput out) throws IOException {
out.writeDouble(trigramLambda);
out.writeDouble(bigramLambda);
out.writeDouble(unigramLambda);
}
public double getTrigramLambda() {
return this.trigramLambda;
}
public double getBigramLambda() {
return this.bigramLambda;
}
public double getUnigramLambda() {
return this.unigramLambda;
}
@Override
protected XContentBuilder innerToXContent(XContentBuilder builder, Params params) throws IOException {
builder.field(TRIGRAM_FIELD.getPreferredName(), trigramLambda);
builder.field(BIGRAM_FIELD.getPreferredName(), bigramLambda);
builder.field(UNIGRAM_FIELD.getPreferredName(), unigramLambda);
return builder;
}
@Override
public String getWriteableName() {
return NAME;
}
@Override
protected boolean doEquals(SmoothingModel other) {
final LinearInterpolation otherModel = (LinearInterpolation) other;
return Objects.equals(trigramLambda, otherModel.trigramLambda) &&
Objects.equals(bigramLambda, otherModel.bigramLambda) &&
Objects.equals(unigramLambda, otherModel.unigramLambda);
}
@Override
protected int doHashCode() {
return Objects.hash(trigramLambda, bigramLambda, unigramLambda);
}
public static LinearInterpolation fromXContent(XContentParser parser) throws IOException {
XContentParser.Token token;
String fieldName = null;
double trigramLambda = 0.0;
double bigramLambda = 0.0;
double unigramLambda = 0.0;
while ((token = parser.nextToken()) != Token.END_OBJECT) {
if (token == XContentParser.Token.FIELD_NAME) {
fieldName = parser.currentName();
} else if (token.isValue()) {
if (TRIGRAM_FIELD.match(fieldName)) {
trigramLambda = parser.doubleValue();
if (trigramLambda < 0) {
throw new IllegalArgumentException("trigram_lambda must be positive");
}
} else if (BIGRAM_FIELD.match(fieldName)) {
bigramLambda = parser.doubleValue();
if (bigramLambda < 0) {
throw new IllegalArgumentException("bigram_lambda must be positive");
}
} else if (UNIGRAM_FIELD.match(fieldName)) {
unigramLambda = parser.doubleValue();
if (unigramLambda < 0) {
throw new IllegalArgumentException("unigram_lambda must be positive");
}
} else {
throw new IllegalArgumentException(
"suggester[phrase][smoothing][linear] doesn't support field [" + fieldName + "]");
}
} else {
throw new ParsingException(parser.getTokenLocation(),
"[" + NAME + "] unknown token [" + token + "] after [" + fieldName + "]");
}
}
return new LinearInterpolation(trigramLambda, bigramLambda, unigramLambda);
}
@Override
public WordScorerFactory buildWordScorerFactory() {
return (IndexReader reader, Terms terms, String field, double realWordLikelyhood, BytesRef separator) ->
new LinearInterpolatingScorer(reader, terms, field, realWordLikelyhood, separator, trigramLambda, bigramLambda,
unigramLambda);
}
}