org.apache.lucene.analysis.ja.JapaneseTokenizerFactory Maven / Gradle / Ivy
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/*
* 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.analysis.ja;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.Reader;
import java.nio.charset.Charset;
import java.nio.charset.CharsetDecoder;
import java.nio.charset.CodingErrorAction;
import java.util.Locale;
import java.util.Map;
import org.apache.lucene.analysis.ja.JapaneseTokenizer.Mode;
import org.apache.lucene.analysis.ja.dict.UserDictionary;
import org.apache.lucene.analysis.util.TokenizerFactory;
import org.apache.lucene.util.AttributeFactory;
import org.apache.lucene.util.IOUtils;
import org.apache.lucene.analysis.util.ResourceLoader;
import org.apache.lucene.analysis.util.ResourceLoaderAware;
/**
* Factory for {@link org.apache.lucene.analysis.ja.JapaneseTokenizer}.
*
* <fieldType name="text_ja" class="solr.TextField">
* <analyzer>
* <tokenizer class="solr.JapaneseTokenizerFactory"
* mode="NORMAL"
* userDictionary="user.txt"
* userDictionaryEncoding="UTF-8"
* discardPunctuation="true"
* />
* <filter class="solr.JapaneseBaseFormFilterFactory"/>
* </analyzer>
* </fieldType>
*
*
* Additional expert user parameters nBestCost and nBestExamples can be
* used to include additional searchable tokens that those most likely
* according to the statistical model. A typical use-case for this is to
* improve recall and make segmentation more resilient to mistakes.
* The feature can also be used to get a decompounding effect.
*
* The nBestCost parameter specifies an additional Viterbi cost, and
* when used, JapaneseTokenizer will include all tokens in Viterbi paths
* that are within the nBestCost value of the best path.
*
* Finding a good value for nBestCost can be difficult to do by hand. The
* nBestExamples parameter can be used to find an nBestCost value based on
* examples with desired segmentation outcomes.
*
* For example, a value of /箱根山-箱根/成田空港-成田/ indicates that in
* the texts, 箱根山 (Mt. Hakone) and 成田空港 (Narita Airport) we'd like
* a cost that gives is us 箱根 (Hakone) and 成田 (Narita). Notice that
* costs are estimated for each example individually, and the maximum
* nBestCost found across all examples is used.
*
* If both nBestCost and nBestExamples is used in a configuration,
* the largest value of the two is used.
*
* Parameters nBestCost and nBestExamples work with all tokenizer
* modes, but it makes the most sense to use them with NORMAL mode.
*/
public class JapaneseTokenizerFactory extends TokenizerFactory implements ResourceLoaderAware {
private static final String MODE = "mode";
private static final String USER_DICT_PATH = "userDictionary";
private static final String USER_DICT_ENCODING = "userDictionaryEncoding";
private static final String DISCARD_PUNCTUATION = "discardPunctuation"; // Expert option
private static final String NBEST_COST = "nBestCost";
private static final String NBEST_EXAMPLES = "nBestExamples";
private UserDictionary userDictionary;
private final Mode mode;
private final boolean discardPunctuation;
private final String userDictionaryPath;
private final String userDictionaryEncoding;
/* Example string for NBEST output.
* its form as:
* nbestExamples := [ / ] example [ / example ]... [ / ]
* example := TEXT - TOKEN
* TEXT := input text
* TOKEN := token should be in nbest result
* Ex. /箱根山-箱根/成田空港-成田/
* When the result tokens are "箱根山", "成田空港" in NORMAL mode,
* /箱根山-箱根/成田空港-成田/ requests "箱根" and "成田" to be in the result in NBEST output.
*/
private final String nbestExamples;
private int nbestCost = -1;
/** Creates a new JapaneseTokenizerFactory */
public JapaneseTokenizerFactory(Map args) {
super(args);
mode = Mode.valueOf(get(args, MODE, JapaneseTokenizer.DEFAULT_MODE.toString()).toUpperCase(Locale.ROOT));
userDictionaryPath = args.remove(USER_DICT_PATH);
userDictionaryEncoding = args.remove(USER_DICT_ENCODING);
discardPunctuation = getBoolean(args, DISCARD_PUNCTUATION, true);
nbestCost = getInt(args, NBEST_COST, 0);
nbestExamples = args.remove(NBEST_EXAMPLES);
if (!args.isEmpty()) {
throw new IllegalArgumentException("Unknown parameters: " + args);
}
}
@Override
public void inform(ResourceLoader loader) throws IOException {
if (userDictionaryPath != null) {
try (InputStream stream = loader.openResource(userDictionaryPath)) {
String encoding = userDictionaryEncoding;
if (encoding == null) {
encoding = IOUtils.UTF_8;
}
CharsetDecoder decoder = Charset.forName(encoding).newDecoder()
.onMalformedInput(CodingErrorAction.REPORT)
.onUnmappableCharacter(CodingErrorAction.REPORT);
Reader reader = new InputStreamReader(stream, decoder);
userDictionary = UserDictionary.open(reader);
}
} else {
userDictionary = null;
}
}
@Override
public JapaneseTokenizer create(AttributeFactory factory) {
JapaneseTokenizer t = new JapaneseTokenizer(factory, userDictionary, discardPunctuation, mode);
if (nbestExamples != null) {
nbestCost = Math.max(nbestCost, t.calcNBestCost(nbestExamples));
}
t.setNBestCost(nbestCost);
return t;
}
}