如何在Lucene 3.5.0中提取文档术语向量

我正在使用Lucene 3.5.0，我想输出每个文档的术语向量。 例如，我想知道所有文档和每个特定文档中术语的频率。 我的索引代码是：

import java.io.FileFilter; import java.io.FileReader; import java.io.IOException; import java.io.File; import java.io.FileReader; import java.io.BufferedReader; import org.apache.lucene.index.IndexWriter; import org.apache.lucene.document.Field; import org.apache.lucene.document.Document; import org.apache.lucene.store.RAMDirectory; import org.apache.lucene.analysis.standard.StandardAnalyzer; import org.apache.lucene.store.Directory; import org.apache.lucene.store.FSDirectory; import org.apache.lucene.util.Version; public class Indexer { public static void main(String[] args) throws Exception { if (args.length != 2) { throw new IllegalArgumentException("Usage: java " + Indexer.class.getName() + "  "); } String indexDir = args[0]; String dataDir = args[1]; long start = System.currentTimeMillis(); Indexer indexer = new Indexer(indexDir); int numIndexed; try { numIndexed = indexer.index(dataDir, new TextFilesFilter()); } finally { indexer.close(); } long end = System.currentTimeMillis(); System.out.println("Indexing " + numIndexed + " files took " + (end - start) + " milliseconds"); } private IndexWriter writer; public Indexer(String indexDir) throws IOException { Directory dir = FSDirectory.open(new File(indexDir)); writer = new IndexWriter(dir, new StandardAnalyzer(Version.LUCENE_35), true, IndexWriter.MaxFieldLength.UNLIMITED); } public void close() throws IOException { writer.close(); } public int index(String dataDir, FileFilter filter) throws Exception { File[] files = new File(dataDir).listFiles(); for (File f: files) { if (!f.isDirectory() && !f.isHidden() && f.exists() && f.canRead() && (filter == null || filter.accept(f))) { BufferedReader inputStream = new BufferedReader(new FileReader(f.getName())); String url = inputStream.readLine(); inputStream.close(); indexFile(f, url); } } return writer.numDocs(); } private static class TextFilesFilter implements FileFilter { public boolean accept(File path) { return path.getName().toLowerCase().endsWith(".txt"); } } protected Document getDocument(File f, String url) throws Exception { Document doc = new Document(); doc.add(new Field("contents", new FileReader(f))); doc.add(new Field("urls", url, Field.Store.YES, Field.Index.NOT_ANALYZED)); doc.add(new Field("filename", f.getName(), Field.Store.YES, Field.Index.NOT_ANALYZED)); doc.add(new Field("fullpath", f.getCanonicalPath(), Field.Store.YES, Field.Index.NOT_ANALYZED)); return doc; } private void indexFile(File f, String url) throws Exception { System.out.println("Indexing " + f.getCanonicalPath()); Document doc = getDocument(f, url); writer.addDocument(doc); } } 

任何人都可以帮我写一个程序来做那个吗？ 谢谢。

Answer 1

首先，您不需要存储术语向量，以便仅知道文档中术语的频率。 然而，Lucene将这些数字存储在TF-IDF计算中。 您可以通过调用IndexReader.termDocs(term)并迭代结果IndexReader.termDocs(term)访问此信息。

如果您还有其他目的并且实际上需要访问术语向量，那么您需要通过将Field.TermVector.YES作为Field构造函数的最后一个参数传递来告诉Lucene存储它们。 然后，您可以使用IndexReader.getTermFreqVector()检索向量。

Answer 2

我在Lucene核心3.0.3上，但我希望API非常相似。 此方法将为一组给定的文档编号和一个感兴趣的字段列表总计一个术语频率图，忽略停用词。

  /** * Sums the term frequency vector of each document into a single term frequency map * @param indexReader the index reader, the document numbers are specific to this reader * @param docNumbers document numbers to retrieve frequency vectors from * @param fieldNames field names to retrieve frequency vectors from * @param stopWords terms to ignore * @return a map of each term to its frequency * @throws IOException */ private Map getTermFrequencyMap(IndexReader indexReader, List docNumbers, String[] fieldNames, Set stopWords) throws IOException { Map totalTfv = new HashMap(1024); for (Integer docNum : docNumbers) { for (String fieldName : fieldNames) { TermFreqVector tfv = indexReader.getTermFreqVector(docNum, fieldName); if (tfv == null) { // ignore empty fields continue; } String terms[] = tfv.getTerms(); int termCount = terms.length; int freqs[] = tfv.getTermFrequencies(); for (int t=0; t < termCount; t++) { String term = terms[t]; int freq = freqs[t]; // filter out single-letter words and stop words if (StringUtils.length(term) < 2 || stopWords.contains(term)) { continue; // stop } Integer totalFreq = totalTfv.get(term); totalFreq = (totalFreq == null) ? freq : freq + totalFreq; totalTfv.put(term, totalFreq); } } } return totalTfv; }