/*

 * 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.

 */

/**

 * <p>Provides algorithms for string similarity.</p>

 *

 * <p>The algorithms that implement the EditDistance interface follow the same

 * simple principle: the more similar (closer) strings are, lower is the distance.

 * For example, the words house and hose are closer than house and trousers.</p>

 *

 * <p>The following algorithms are available at the moment:</p>

 *

 * <ul>

 * <li>{@link org.apache.commons.text.similarity.CosineDistance Cosine Distance}</li>

 * <li>{@link org.apache.commons.text.similarity.CosineSimilarity Cosine Similarity}</li>

 * <li>{@link org.apache.commons.text.similarity.FuzzyScore Fuzzy Score}</li>

 * <li>{@link org.apache.commons.text.similarity.HammingDistance Hamming Distance}</li>

 * <li>{@link org.apache.commons.text.similarity.JaroWinklerDistance Jaro-Winkler Distance}</li>

 * <li>{@link org.apache.commons.text.similarity.JaroWinklerSimilarity Jaro-Winkler Similarity}</li>

 * <li>{@link org.apache.commons.text.similarity.LevenshteinDistance Levenshtein Distance}</li>

 * <li>{@link org.apache.commons.text.similarity.LongestCommonSubsequenceDistance

 * Longest Common Subsequence Distance}</li>

 * </ul>

 *

 * <p>The {@link org.apache.commons.text.similarity.CosineDistance Cosine Distance}

 * utilises a {@link org.apache.commons.text.similarity.RegexTokenizer regular expression tokenizer (\w+)}.

 * And the {@link org.apache.commons.text.similarity.LevenshteinDistance Levenshtein Distance}'s

 * behavior can be changed to take into consideration a maximum throughput.</p>

 *

 * @since 1.0

 */

package org.apache.commons.text.similarity;