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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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package org.apache.lucene.analysis.cn.smart;
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import java.io.IOException;
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import java.io.Reader;
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import java.util.Collections;
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import org.apache.lucene.analysis.Analyzer;
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import org.apache.lucene.analysis.PorterStemFilter;
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import org.apache.lucene.analysis.StopFilter;
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import org.apache.lucene.analysis.TokenStream;
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import org.apache.lucene.analysis.Tokenizer;
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import org.apache.lucene.analysis.WordlistLoader;
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import org.apache.lucene.analysis.cn.smart.SentenceTokenizer;
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import org.apache.lucene.analysis.cn.smart.WordTokenFilter;
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import org.apache.lucene.analysis.CharArraySet;
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import org.apache.lucene.util.IOUtils;
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import org.apache.lucene.util.Version;
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* SmartChineseAnalyzer is an analyzer for Chinese or mixed Chinese-English text.
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* The analyzer uses probabilistic knowledge to find the optimal word segmentation for Simplified Chinese text.
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* The text is first broken into sentences, then each sentence is segmented into words.
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* Segmentation is based upon the <a href="http://en.wikipedia.org/wiki/Hidden_Markov_Model">Hidden Markov Model</a>.
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* A large training corpus was used to calculate Chinese word frequency probability.
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* This analyzer requires a dictionary to provide statistical data.
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* SmartChineseAnalyzer has an included dictionary out-of-box.
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* The included dictionary data is from <a href="http://www.ictclas.org">ICTCLAS1.0</a>.
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* Thanks to ICTCLAS for their hard work, and for contributing the data under the Apache 2 License!
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* @lucene.experimental
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public final class SmartChineseAnalyzer extends Analyzer {
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private final Set<?> stopWords;
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private static final String DEFAULT_STOPWORD_FILE = "stopwords.txt";
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private static final String STOPWORD_FILE_COMMENT = "//";
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* Returns an unmodifiable instance of the default stop-words set.
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* @return an unmodifiable instance of the default stop-words set.
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public static CharArraySet getDefaultStopSet(){
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return DefaultSetHolder.DEFAULT_STOP_SET;
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* Atomically loads the DEFAULT_STOP_SET in a lazy fashion once the outer class
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* accesses the static final set the first time.;
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private static class DefaultSetHolder {
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static final CharArraySet DEFAULT_STOP_SET;
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DEFAULT_STOP_SET = loadDefaultStopWordSet();
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} catch (IOException ex) {
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// default set should always be present as it is part of the
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throw new RuntimeException("Unable to load default stopword set");
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static CharArraySet loadDefaultStopWordSet() throws IOException {
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// make sure it is unmodifiable as we expose it in the outer class
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return org.apache.lucene.analysis.CharArraySet.unmodifiableSet(WordlistLoader.getWordSet(IOUtils
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.getDecodingReader(SmartChineseAnalyzer.class, DEFAULT_STOPWORD_FILE,
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IOUtils.CHARSET_UTF_8), STOPWORD_FILE_COMMENT,
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Version.LUCENE_CURRENT));
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private final Version matchVersion;
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* Create a new SmartChineseAnalyzer, using the default stopword list.
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public SmartChineseAnalyzer(Version matchVersion) {
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this(matchVersion, true);
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* Create a new SmartChineseAnalyzer, optionally using the default stopword list.
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* The included default stopword list is simply a list of punctuation.
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* If you do not use this list, punctuation will not be removed from the text!
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* @param useDefaultStopWords true to use the default stopword list.
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public SmartChineseAnalyzer(Version matchVersion, boolean useDefaultStopWords) {
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stopWords = useDefaultStopWords ? DefaultSetHolder.DEFAULT_STOP_SET
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: Collections.EMPTY_SET;
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this.matchVersion = matchVersion;
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* Create a new SmartChineseAnalyzer, using the provided {@link Set} of stopwords.
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* Note: the set should include punctuation, unless you want to index punctuation!
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* @param stopWords {@link Set} of stopwords to use.
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public SmartChineseAnalyzer(Version matchVersion, Set stopWords) {
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this.stopWords = stopWords==null?Collections.EMPTY_SET:stopWords;
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this.matchVersion = matchVersion;
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public TokenStream tokenStream(String fieldName, Reader reader) {
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TokenStream result = new SentenceTokenizer(reader);
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result = new WordTokenFilter(result);
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// result = new LowerCaseFilter(result);
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// LowerCaseFilter is not needed, as SegTokenFilter lowercases Basic Latin text.
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// The porter stemming is too strict, this is not a bug, this is a feature:)
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result = new PorterStemFilter(result);
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if (!stopWords.isEmpty()) {
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result = new StopFilter(matchVersion, result, stopWords, false);
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private static final class SavedStreams {
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Tokenizer tokenStream;
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TokenStream filteredTokenStream;
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public TokenStream reusableTokenStream(String fieldName, Reader reader)
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SavedStreams streams = (SavedStreams) getPreviousTokenStream();
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if (streams == null) {
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streams = new SavedStreams();
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setPreviousTokenStream(streams);
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streams.tokenStream = new SentenceTokenizer(reader);
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streams.filteredTokenStream = new WordTokenFilter(streams.tokenStream);
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streams.filteredTokenStream = new PorterStemFilter(streams.filteredTokenStream);
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if (!stopWords.isEmpty()) {
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streams.filteredTokenStream = new StopFilter(matchVersion, streams.filteredTokenStream, stopWords, false);
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streams.tokenStream.reset(reader);
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streams.filteredTokenStream.reset(); // reset WordTokenFilter's state
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return streams.filteredTokenStream;