opennlp.tools.util.featuregen.CharacterNgramFeatureGenerator Maven / Gradle / Ivy
/*
* 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 opennlp.tools.util.featuregen;
import java.util.List;
import opennlp.tools.ngram.NGramModel;
import opennlp.tools.util.StringList;
import opennlp.tools.util.StringUtil;
/**
* The {@link CharacterNgramFeatureGenerator} uses character ngrams to
* generate features about each token.
* The minimum and maximum length can be specified.
*/
public class CharacterNgramFeatureGenerator implements AdaptiveFeatureGenerator {
private final int minLength;
private final int maxLength;
public CharacterNgramFeatureGenerator(int minLength, int maxLength) {
this.minLength = minLength;
this.maxLength = maxLength;
}
/**
* Initializes the current instance with min 2 length and max 5 length of ngrams.
*/
public CharacterNgramFeatureGenerator() {
this(2, 5);
}
public void createFeatures(List features, String[] tokens, int index, String[] preds) {
NGramModel model = new NGramModel();
model.add(tokens[index], minLength, maxLength);
for (StringList tokenList : model) {
if (tokenList.size() > 0) {
features.add("ng=" + StringUtil.toLowerCase(tokenList.getToken(0)));
}
}
}
}