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    <p>As Julia points out <a href="http://sujitpal.blogspot.ch/2011/10/computing-document-similarity-using.html" rel="noreferrer">Sujit Pal's example</a> is very useful but the Lucene 4 API has substantial changes. Here is a version rewritten for Lucene 4. </p> <pre><code>import java.io.IOException; import java.util.*; import org.apache.commons.math3.linear.*; import org.apache.lucene.analysis.Analyzer; import org.apache.lucene.analysis.core.SimpleAnalyzer; import org.apache.lucene.document.*; import org.apache.lucene.document.Field.Store; import org.apache.lucene.index.*; import org.apache.lucene.store.*; import org.apache.lucene.util.*; public class CosineDocumentSimilarity { public static final String CONTENT = "Content"; private final Set&lt;String&gt; terms = new HashSet&lt;&gt;(); private final RealVector v1; private final RealVector v2; CosineDocumentSimilarity(String s1, String s2) throws IOException { Directory directory = createIndex(s1, s2); IndexReader reader = DirectoryReader.open(directory); Map&lt;String, Integer&gt; f1 = getTermFrequencies(reader, 0); Map&lt;String, Integer&gt; f2 = getTermFrequencies(reader, 1); reader.close(); v1 = toRealVector(f1); v2 = toRealVector(f2); } Directory createIndex(String s1, String s2) throws IOException { Directory directory = new RAMDirectory(); Analyzer analyzer = new SimpleAnalyzer(Version.LUCENE_CURRENT); IndexWriterConfig iwc = new IndexWriterConfig(Version.LUCENE_CURRENT, analyzer); IndexWriter writer = new IndexWriter(directory, iwc); addDocument(writer, s1); addDocument(writer, s2); writer.close(); return directory; } /* Indexed, tokenized, stored. */ public static final FieldType TYPE_STORED = new FieldType(); static { TYPE_STORED.setIndexed(true); TYPE_STORED.setTokenized(true); TYPE_STORED.setStored(true); TYPE_STORED.setStoreTermVectors(true); TYPE_STORED.setStoreTermVectorPositions(true); TYPE_STORED.freeze(); } void addDocument(IndexWriter writer, String content) throws IOException { Document doc = new Document(); Field field = new Field(CONTENT, content, TYPE_STORED); doc.add(field); writer.addDocument(doc); } double getCosineSimilarity() { return (v1.dotProduct(v2)) / (v1.getNorm() * v2.getNorm()); } public static double getCosineSimilarity(String s1, String s2) throws IOException { return new CosineDocumentSimilarity(s1, s2).getCosineSimilarity(); } Map&lt;String, Integer&gt; getTermFrequencies(IndexReader reader, int docId) throws IOException { Terms vector = reader.getTermVector(docId, CONTENT); TermsEnum termsEnum = null; termsEnum = vector.iterator(termsEnum); Map&lt;String, Integer&gt; frequencies = new HashMap&lt;&gt;(); BytesRef text = null; while ((text = termsEnum.next()) != null) { String term = text.utf8ToString(); int freq = (int) termsEnum.totalTermFreq(); frequencies.put(term, freq); terms.add(term); } return frequencies; } RealVector toRealVector(Map&lt;String, Integer&gt; map) { RealVector vector = new ArrayRealVector(terms.size()); int i = 0; for (String term : terms) { int value = map.containsKey(term) ? map.get(term) : 0; vector.setEntry(i++, value); } return (RealVector) vector.mapDivide(vector.getL1Norm()); } } </code></pre>
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    1. POget cosine similarity between two documents in lucene
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    1. COHas VecTextField been taken from [this](http://stackoverflow.com/questions/11945728/how-to-use-termvector-lucene-4-0) question?
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    2. CO@o_nix - yes you are right. Thanks. Now fixed
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    3. COI'm test this with Sujit Pal example : Document#0: Mitral valve surgery - minimally invasive (31825) Document#1: Mitral valve surgery - open (31835) Document#2: Laryngectomy (31706) but it got difference reuslt ! can you explain why Thanks
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