/**
* 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.cn.smart;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.io.Reader;
import java.util.Set;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.PorterStemFilter;
import org.apache.lucene.analysis.StopFilter;
import org.apache.lucene.analysis.TokenStream;
import org.apache.lucene.analysis.Tokenizer;
import org.apache.lucene.analysis.WordlistLoader;
import org.apache.lucene.analysis.cn.smart.SentenceTokenizer;
import org.apache.lucene.analysis.cn.smart.WordTokenFilter;
import org.apache.lucene.util.Version;
/**
* <p>
* SmartChineseAnalyzer is an analyzer for Chinese or mixed Chinese-English text.
* The analyzer uses probabilistic knowledge to find the optimal word segmentation for Simplified Chinese text.
* The text is first broken into sentences, then each sentence is segmented into words.
* </p>
* <p>
* Segmentation is based upon the <a href="http://en.wikipedia.org/wiki/Hidden_Markov_Model">Hidden Markov Model</a>.
* A large training corpus was used to calculate Chinese word frequency probability.
* </p>
* <p>
* This analyzer requires a dictionary to provide statistical data.
* SmartChineseAnalyzer has an included dictionary out-of-box.
* </p>
* <p>
* The included dictionary data is from <a href="http://www.ictclas.org">ICTCLAS1.0</a>.
* Thanks to ICTCLAS for their hard work, and for contributing the data under the Apache 2 License!
* </p>
* <p><font color="#FF0000">
* WARNING: The status of the analyzers/smartcn <b>analysis.cn.smart</b> package is experimental.
* The APIs and file formats introduced here might change in the future and will not be
* supported anymore in such a case.</font>
* </p>
*/
public class SmartChineseAnalyzer extends Analyzer {
private final Set stopWords;
private final Version matchVersion;
/**
* Create a new SmartChineseAnalyzer, using the default stopword list.
*
* @deprecated Use {@link #SmartChineseAnalyzer(Version)} instead
*/
public SmartChineseAnalyzer() {
this(Version.LUCENE_24, true);
}
/**
* Create a new SmartChineseAnalyzer, using the default stopword list.
*/
public SmartChineseAnalyzer(Version matchVersion) {
this(matchVersion, true);
}
/**
* <p>
* Create a new SmartChineseAnalyzer, optionally using the default stopword list.
* </p>
* <p>
* The included default stopword list is simply a list of punctuation.
* If you do not use this list, punctuation will not be removed from the text!
* </p>
*
* @param useDefaultStopWords true to use the default stopword list.
*
* @deprecated Use {@link #SmartChineseAnalyzer(Version, boolean)} instead
*/
public SmartChineseAnalyzer(boolean useDefaultStopWords) {
this(Version.LUCENE_24, useDefaultStopWords);
}
/**
* <p>
* Create a new SmartChineseAnalyzer, optionally using the default stopword list.
* </p>
* <p>
* The included default stopword list is simply a list of punctuation.
* If you do not use this list, punctuation will not be removed from the text!
* </p>
*
* @param useDefaultStopWords true to use the default stopword list.
*/
public SmartChineseAnalyzer(Version matchVersion, boolean useDefaultStopWords) {
this.matchVersion = matchVersion;
if (useDefaultStopWords) {
try {
InputStream stream = this.getClass().getResourceAsStream("stopwords.txt");
InputStreamReader reader = new InputStreamReader(stream, "UTF-8");
stopWords = WordlistLoader.getWordSet(reader, "//");
} catch (IOException e) {
// TODO: throw IOException
throw new RuntimeException(e);
}
}else{
stopWords = null;
}
}
/**
* <p>
* Create a new SmartChineseAnalyzer, using the provided {@link Set} of stopwords.
* </p>
* <p>
* Note: the set should include punctuation, unless you want to index punctuation!
* </p>
* @param stopWords {@link Set} of stopwords to use.
*
* @deprecated Use {@link #SmartChineseAnalyzer(Version, Set)} instead
*/
public SmartChineseAnalyzer(Set stopWords) {
this(Version.LUCENE_24, stopWords);
}
/**
* <p>
* Create a new SmartChineseAnalyzer, using the provided {@link Set} of stopwords.
* </p>
* <p>
* Note: the set should include punctuation, unless you want to index punctuation!
* </p>
* @param stopWords {@link Set} of stopwords to use.
*/
public SmartChineseAnalyzer(Version matchVersion, Set stopWords) {
this.stopWords = stopWords;
this.matchVersion = matchVersion;
}
public TokenStream tokenStream(String fieldName, Reader reader) {
TokenStream result = new SentenceTokenizer(reader);
result = new WordTokenFilter(result);
// result = new LowerCaseFilter(result);
// LowerCaseFilter is not needed, as SegTokenFilter lowercases Basic Latin text.
// The porter stemming is too strict, this is not a bug, this is a feature:)
result = new PorterStemFilter(result);
if (stopWords != null) {
result = new StopFilter(StopFilter.getEnablePositionIncrementsVersionDefault(matchVersion),
result, stopWords, false);
}
return result;
}
private static final class SavedStreams {
Tokenizer tokenStream;
TokenStream filteredTokenStream;
}
public TokenStream reusableTokenStream(String fieldName, Reader reader)
throws IOException {
SavedStreams streams = (SavedStreams) getPreviousTokenStream();
if (streams == null) {
streams = new SavedStreams();
setPreviousTokenStream(streams);
streams.tokenStream = new SentenceTokenizer(reader);
streams.filteredTokenStream = new WordTokenFilter(streams.tokenStream);
streams.filteredTokenStream = new PorterStemFilter(streams.filteredTokenStream);
if (stopWords != null) {
streams.filteredTokenStream = new StopFilter(StopFilter.getEnablePositionIncrementsVersionDefault(matchVersion),
streams.filteredTokenStream, stopWords, false);
}
} else {
streams.tokenStream.reset(reader);
streams.filteredTokenStream.reset(); // reset WordTokenFilter's state
}
return streams.filteredTokenStream;
}
}