--- /dev/null
+/**
+ * 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.Reader;
+import java.util.Collections;
+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.analysis.CharArraySet;
+import org.apache.lucene.util.IOUtils;
+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>
+ * @lucene.experimental
+ */
+public final class SmartChineseAnalyzer extends Analyzer {
+
+ private final Set<?> stopWords;
+
+ private static final String DEFAULT_STOPWORD_FILE = "stopwords.txt";
+
+ private static final String STOPWORD_FILE_COMMENT = "//";
+
+ /**
+ * Returns an unmodifiable instance of the default stop-words set.
+ * @return an unmodifiable instance of the default stop-words set.
+ */
+ public static CharArraySet getDefaultStopSet(){
+ return DefaultSetHolder.DEFAULT_STOP_SET;
+ }
+
+ /**
+ * Atomically loads the DEFAULT_STOP_SET in a lazy fashion once the outer class
+ * accesses the static final set the first time.;
+ */
+ private static class DefaultSetHolder {
+ static final CharArraySet DEFAULT_STOP_SET;
+
+ static {
+ try {
+ DEFAULT_STOP_SET = loadDefaultStopWordSet();
+ } catch (IOException ex) {
+ // default set should always be present as it is part of the
+ // distribution (JAR)
+ throw new RuntimeException("Unable to load default stopword set");
+ }
+ }
+
+ static CharArraySet loadDefaultStopWordSet() throws IOException {
+ // make sure it is unmodifiable as we expose it in the outer class
+ return org.apache.lucene.analysis.CharArraySet.unmodifiableSet(WordlistLoader.getWordSet(IOUtils
+ .getDecodingReader(SmartChineseAnalyzer.class, DEFAULT_STOPWORD_FILE,
+ IOUtils.CHARSET_UTF_8), STOPWORD_FILE_COMMENT,
+ Version.LUCENE_CURRENT));
+ }
+ }
+
+ private final Version matchVersion;
+
+ /**
+ * 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.
+ */
+ public SmartChineseAnalyzer(Version matchVersion, boolean useDefaultStopWords) {
+ stopWords = useDefaultStopWords ? DefaultSetHolder.DEFAULT_STOP_SET
+ : Collections.EMPTY_SET;
+ this.matchVersion = matchVersion;
+ }
+
+ /**
+ * <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==null?Collections.EMPTY_SET:stopWords;
+ this.matchVersion = matchVersion;
+ }
+
+ @Override
+ 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.isEmpty()) {
+ result = new StopFilter(matchVersion, result, stopWords, false);
+ }
+ return result;
+ }
+
+ private static final class SavedStreams {
+ Tokenizer tokenStream;
+ TokenStream filteredTokenStream;
+ }
+
+ @Override
+ 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.isEmpty()) {
+ streams.filteredTokenStream = new StopFilter(matchVersion, streams.filteredTokenStream, stopWords, false);
+ }
+ } else {
+ streams.tokenStream.reset(reader);
+ streams.filteredTokenStream.reset(); // reset WordTokenFilter's state
+ }
+
+ return streams.filteredTokenStream;
+ }
+}
fnp / pylucene.git / blobdiff