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Added a public, extensible scoring API. 

git-svn-id: https://svn.apache.org/repos/asf/lucene/java/trunk@149885 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Doug Cutting 2002-11-07 17:31:27 +00:00
parent 98330b5030
commit 6772e7567d
27 changed files with 609 additions and 145 deletions
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3
CHANGES.txt
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@ -93,6 +93,9 @@ $Id$
17. Added Russian Analyzer.
(Boris Okner via otis)
18. Added a public, extensible scoring API. For details, see the
javadoc for org.apache.lucene.search.Similarity.
1.2 RC6

32
build.xml
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@ -12,14 +12,21 @@
<!-- Build classpath -->
<path id="classpath">
<pathelement location="${build.classes}"/>
<pathelement location="${build.demo.classes}"/>
<pathelement location="${build.test.classes}"/>
<pathelement location="."/>
<fileset dir="lib">
<include name="*.jar" />
</fileset>
</path>
<path id="demo.classpath">
<path refid="classpath"/>
<pathelement location="${build.demo.classes}"/>
</path>
<path id="test.classpath">
<path refid="demo.classpath"/>
<pathelement location="${build.test.classes}"/>
</path>
<path id="junit.classpath">
<pathelement location="${junit.classes}" />
<pathelement location="${build.classes}"/>
@ -245,7 +252,7 @@ Implementation-Vendor: Lucene
includes="**/*.java"
destdir="${build.demo.classes}"
debug="${debug}">
<classpath refid="classpath"/>
<classpath refid="demo.classpath"/>
</javac>
</target>
@ -255,23 +262,14 @@ Implementation-Vendor: Lucene
<!-- -->
<!-- ================================================================== -->
<target name="test" depends="compile,demo">
<mkdir dir="${build.test}"/>
<copy todir="${build.test.src}">
<fileset dir="${test.src}">
<include name="**/*.java"/>
</fileset>
</copy>
<mkdir dir="${build.test.classes}"/>
<javac
encoding="${build.encoding}"
srcdir="${build.test.src}"
srcdir="${test.src}"
includes="**/*.java"
destdir="${build.test.classes}"
debug="${debug}">
<classpath refid="classpath"/>
<classpath refid="test.classpath"/>
</javac>
</target>
@ -295,7 +293,7 @@ Implementation-Vendor: Lucene
includes="**/*.java"
destdir="${junit.classes}"
debug="${debug}">
<classpath refid="classpath"/>
<classpath refid="test.classpath"/>
</javac>
<junit printsummary="yes" haltonfailure="no" >
@ -565,7 +563,7 @@ Implementation-Vendor: Lucene
<!-- ================================================================== -->
<!-- -->
<!-- ================================================================== -->
<target name="clean" depends="init">
<target name="clean">
<delete dir="${build.dir}"/>
<delete dir="${dist.dir}"/>
<delete file="${basedir}/${final.name}.tar"/>

1
default.properties
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@ -50,7 +50,6 @@ build.docweb = ${build.dir}/docweb
build.docweb.war.name = lucenedocweb
build.test = ${build.dir}/test
build.test.src = ${build.test}/src
build.test.classes = ${build.test}/classes
junit.src = ${basedir}/src/test

5
src/java/org/apache/lucene/analysis/ru/package.html Normal file
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@ -0,0 +1,5 @@
<html>
<body>
Support for indexing and searching Russian text.
</body>
</html>

4
src/java/org/apache/lucene/document/Field.java
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@ -85,13 +85,13 @@ public final class Field implements java.io.Serializable {
* <p>The boost is multiplied by {@link Document#getBoost()} of the document
* containing this field. If a document has multiple fields with the same
* name, all such values are multiplied together. This product is then
* multipled by the value {@link Similarity#normalizeLength(int)}, and
* multipled by the value {@link Similarity#lengthNorm(String,int)}, and
* rounded by {@link Similarity#encodeNorm(float)} before it is stored in the
* index. One should attempt to ensure that this product does not overflow
* the range of that encoding.
*
* @see Document#setBoost(float)
* @see Similarity#normalizeLength(int)
* @see Similarity#lengthNorm(String, int)
* @see Similarity#encodeNorm(float)
*/
public void setBoost(float boost) {

17
src/java/org/apache/lucene/index/DocumentWriter.java
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@ -73,13 +73,16 @@ import org.apache.lucene.search.Similarity;
final class DocumentWriter {
private Analyzer analyzer;
private Directory directory;
private Similarity similarity;
private FieldInfos fieldInfos;
private int maxFieldLength;
DocumentWriter(Directory d, Analyzer a, int mfl) {
directory = d;
analyzer = a;
maxFieldLength = mfl;
DocumentWriter(Directory directory, Analyzer analyzer,
Similarity similarity, int maxFieldLength) {
this.directory = directory;
this.analyzer = analyzer;
this.similarity = similarity;
this.maxFieldLength = maxFieldLength;
}
final void addDocument(String segment, Document doc)
@ -320,10 +323,10 @@ final class DocumentWriter {
if (field.isIndexed()) {
int n = fieldInfos.fieldNumber(field.name());
float norm =
fieldBoosts[n] * Similarity.normalizeLength(fieldLengths[n]);
fieldBoosts[n] * similarity.lengthNorm(field.name(),fieldLengths[n]);
OutputStream norms = directory.createFile(segment + ".f" + n);
try {
norms.writeByte(Similarity.encodeNorm(norm));
norms.writeByte(similarity.encodeNorm(norm));
} finally {
norms.close();
}

31
src/java/org/apache/lucene/index/IndexWriter.java
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@ -68,6 +68,8 @@ import org.apache.lucene.store.OutputStream;
import org.apache.lucene.search.Similarity;
import org.apache.lucene.document.Document;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.search.Similarity;
/**
An IndexWriter creates and maintains an index.
@ -89,12 +91,28 @@ public class IndexWriter {
private Directory directory; // where this index resides
private Analyzer analyzer; // how to analyze text
private Similarity similarity = Similarity.getDefault(); // how to normalize
private SegmentInfos segmentInfos = new SegmentInfos(); // the segments
private final Directory ramDirectory = new RAMDirectory(); // for temp segs
private Lock writeLock;
private Similarity similarity;
/** Expert: Set the Similarity implementation used by this IndexWriter.
*
* @see Similarity#setDefault(Similarity)
*/
public void setSimilarity(Similarity similarity) {
this.similarity = similarity;
}
/** Expert: Return the Similarity implementation used by this IndexWriter.
*
* <p>This defaults to the current value of {@link Similarity#getDefault()}.
*/
public Similarity getSimilarity() {
return this.similarity;
}
/** Constructs an IndexWriter for the index in <code>path</code>. Text will
be analyzed with <code>a</code>. If <code>create</code> is true, then a
@ -186,7 +204,7 @@ public class IndexWriter {
/** Adds a document to this index.*/
public void addDocument(Document doc) throws IOException {
DocumentWriter dw =
new DocumentWriter(ramDirectory, analyzer, maxFieldLength);
new DocumentWriter(ramDirectory, analyzer, similarity, maxFieldLength);
String segmentName = newSegmentName();
dw.addDocument(segmentName, doc);
synchronized (this) {
@ -407,13 +425,4 @@ public class IndexWriter {
}
directory.renameFile("deleteable.new", "deletable");
}
/**
* Sets the <code>Similarity</code> implementation to use.
*
* @param sim an instance of a class that implements <code>Similarity</code
*/
public void setSimilarity(Similarity sim) {
similarity = sim;
}
}

8
src/java/org/apache/lucene/search/BooleanQuery.java
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@ -116,20 +116,20 @@ public class BooleanQuery extends Query {
}
}
Scorer scorer(IndexReader reader)
Scorer scorer(IndexReader reader, Similarity similarity)
throws IOException {
if (clauses.size() == 1) { // optimize 1-term queries
BooleanClause c = (BooleanClause)clauses.elementAt(0);
if (!c.prohibited) // just return term scorer
return c.query.scorer(reader);
return c.query.scorer(reader, similarity);
}
BooleanScorer result = new BooleanScorer();
BooleanScorer result = new BooleanScorer(similarity);
for (int i = 0 ; i < clauses.size(); i++) {
BooleanClause c = (BooleanClause)clauses.elementAt(i);
Scorer subScorer = c.query.scorer(reader);
Scorer subScorer = c.query.scorer(reader, similarity);
if (subScorer != null)
result.add(subScorer, c.required, c.prohibited);
else if (c.required)

6
src/java/org/apache/lucene/search/BooleanScorer.java
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@ -70,6 +70,10 @@ final class BooleanScorer extends Scorer {
private int prohibitedMask = 0;
private int nextMask = 1;
BooleanScorer(Similarity similarity) {
super(similarity);
}
static final class SubScorer {
public Scorer scorer;
public boolean required = false;
@ -113,7 +117,7 @@ final class BooleanScorer extends Scorer {
private final void computeCoordFactors() throws IOException {
coordFactors = new float[maxCoord];
for (int i = 0; i < maxCoord; i++)
coordFactors[i] = Similarity.coord(i, maxCoord);
coordFactors[i] = getSimilarity().coord(i, maxCoord);
}
final void score(HitCollector results, int maxDoc) throws IOException {

90
src/java/org/apache/lucene/search/DefaultSimilarity.java Normal file
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@ -0,0 +1,90 @@
package org.apache.lucene.search;
/* ====================================================================
* The Apache Software License, Version 1.1
*
* Copyright (c) 2001 The Apache Software Foundation. All rights
* reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
*
* 3. The end-user documentation included with the redistribution,
* if any, must include the following acknowledgment:
* "This product includes software developed by the
* Apache Software Foundation (http://www.apache.org/)."
* Alternately, this acknowledgment may appear in the software itself,
* if and wherever such third-party acknowledgments normally appear.
*
* 4. The names "Apache" and "Apache Software Foundation" and
* "Apache Lucene" must not be used to endorse or promote products
* derived from this software without prior written permission. For
* written permission, please contact apache@apache.org.
*
* 5. Products derived from this software may not be called "Apache",
* "Apache Lucene", nor may "Apache" appear in their name, without
* prior written permission of the Apache Software Foundation.
*
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
* SUCH DAMAGE.
* ====================================================================
*
* This software consists of voluntary contributions made by many
* individuals on behalf of the Apache Software Foundation. For more
* information on the Apache Software Foundation, please see
* <http://www.apache.org/>.
*/
import org.apache.lucene.document.Document;
/** Expert: Default scoring implementation. */
public class DefaultSimilarity extends Similarity {
/** Implemented as <code>1/sqrt(numTerms)</code>. */
public float lengthNorm(String fieldName, int numTerms) {
return (float)(1.0 / Math.sqrt(numTerms));
}
/** Implemented as <code>1/sqrt(sumOfSquaredWeights)</code>. */
public float queryNorm(float sumOfSquaredWeights) {
return (float)(1.0 / Math.sqrt(sumOfSquaredWeights));
}
/** Implemented as <code>sqrt(freq)</code>. */
public float tf(float freq) {
return (float)Math.sqrt(freq);
}
/** Implemented as <code>1 / (distance + 1)</code>. */
public float sloppyFreq(int distance) {
return 1.0f / (distance + 1);
}
/** Implemented as <code>log(numDocs/(docFreq+1)) + 1</code>. */
public float idf(int docFreq, int numDocs) {
return (float)(Math.log(numDocs/(double)(docFreq+1)) + 1.0);
}
/** Implemented as <code>overlap / maxOverlap</code>. */
public float coord(int overlap, int maxOverlap) {
return overlap / (float)maxOverlap;
}
}

6
src/java/org/apache/lucene/search/ExactPhraseScorer.java
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@ -61,9 +61,9 @@ import org.apache.lucene.index.*;
final class ExactPhraseScorer extends PhraseScorer {
ExactPhraseScorer(TermPositions[] tps, byte[] n, float w)
throws IOException {
super(tps, n, w);
ExactPhraseScorer(TermPositions[] tps, Similarity similarity,
byte[] norms, float weight) throws IOException {
super(tps, similarity, norms, weight);
}
protected final float phraseFreq() throws IOException {

6
src/java/org/apache/lucene/search/MultiTermQuery.java
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@ -85,7 +85,6 @@ public class MultiTermQuery extends Query {
/** Constructs a query for terms matching <code>term</code>. */
public MultiTermQuery(Term term) {
this.term = term;
this.query = query;
}
/** Set the TermEnum to be used */
@ -105,8 +104,9 @@ public class MultiTermQuery extends Query {
}
}
final Scorer scorer(IndexReader reader) throws IOException {
return getQuery().scorer(reader);
final Scorer scorer(IndexReader reader, Similarity similarity)
throws IOException {
return getQuery().scorer(reader, similarity);
}
private final BooleanQuery getQuery() throws IOException {

12
src/java/org/apache/lucene/search/PhrasePrefixQuery.java
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@ -147,7 +147,7 @@ public class PhrasePrefixQuery
_termArrays.add(terms);
}
Scorer scorer(IndexReader reader)
Scorer scorer(IndexReader reader, Similarity similarity)
throws IOException
{
if (_termArrays.size() == 0) // optimize zero-term case
@ -161,7 +161,7 @@ public class PhrasePrefixQuery
for (int i=0; i<terms.length; i++)
boq.add(new TermQuery(terms[i]), false, false);
return boq.scorer(reader);
return boq.scorer(reader, similarity);
}
TermPositions[] tps = new TermPositions[_termArrays.size()];
@ -182,9 +182,11 @@ public class PhrasePrefixQuery
}
if (_slop == 0)
return new ExactPhraseScorer(tps, reader.norms(_field), _weight);
return new ExactPhraseScorer(tps, similarity,
reader.norms(_field), _weight);
else
return new SloppyPhraseScorer(tps, _slop, reader.norms(_field), _weight);
return new SloppyPhraseScorer(tps, similarity, _slop,
reader.norms(_field), _weight);
}
float sumOfSquaredWeights(Searcher searcher)
@ -195,7 +197,7 @@ public class PhrasePrefixQuery
{
Term[] terms = (Term[])i.next();
for (int j=0; j<terms.length; j++)
_idf += Similarity.idf(terms[j], searcher);
_idf += searcher.getSimilarity().idf(terms[j], searcher);
}
_weight = _idf * boost;

17
src/java/org/apache/lucene/search/PhraseQuery.java
View File

@ -108,10 +108,7 @@ public class PhraseQuery extends Query {
}
final float sumOfSquaredWeights(Searcher searcher) throws IOException {
idf = 0.0f;
for (int i = 0; i < terms.size(); i++) // sum term IDFs
idf += Similarity.idf((Term)terms.elementAt(i), searcher);
idf = searcher.getSimilarity().idf(terms, searcher);
weight = idf * boost;
return weight * weight; // square term weights
}
@ -121,7 +118,8 @@ public class PhraseQuery extends Query {
weight *= idf; // factor from document
}
final Scorer scorer(IndexReader reader) throws IOException {
final Scorer scorer(IndexReader reader, Similarity similarity)
throws IOException {
if (terms.size() == 0) // optimize zero-term case
return null;
if (terms.size() == 1) { // optimize one-term case
@ -129,7 +127,8 @@ public class PhraseQuery extends Query {
TermDocs docs = reader.termDocs(term);
if (docs == null)
return null;
return new TermScorer(docs, reader.norms(term.field()), weight);
return new TermScorer(docs, similarity,
reader.norms(term.field()), weight);
}
TermPositions[] tps = new TermPositions[terms.size()];
@ -141,10 +140,12 @@ public class PhraseQuery extends Query {
}
if (slop == 0) // optimize exact case
return new ExactPhraseScorer(tps, reader.norms(field), weight);
return new ExactPhraseScorer(tps, similarity,
reader.norms(field), weight);
else
return
new SloppyPhraseScorer(tps, slop, reader.norms(field), weight);
new SloppyPhraseScorer(tps, similarity, slop,
reader.norms(field), weight);
}

11
src/java/org/apache/lucene/search/PhraseScorer.java
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@ -66,9 +66,11 @@ abstract class PhraseScorer extends Scorer {
protected PhraseQueue pq;
protected PhrasePositions first, last;
PhraseScorer(TermPositions[] tps, byte[] n, float w) throws IOException {
norms = n;
weight = w;
PhraseScorer(TermPositions[] tps, Similarity similarity,
byte[] norms, float weight) throws IOException {
super(similarity);
this.norms = norms;
this.weight = weight;
// use PQ to build a sorted list of PhrasePositions
pq = new PhraseQueue(tps.length);
@ -78,6 +80,7 @@ abstract class PhraseScorer extends Scorer {
}
final void score(HitCollector results, int end) throws IOException {
Similarity similarity = getSimilarity();
while (last.doc < end) { // find doc w/ all the terms
while (first.doc < last.doc) { // scan forward in first
do {
@ -92,7 +95,7 @@ abstract class PhraseScorer extends Scorer {
float freq = phraseFreq(); // check for phrase
if (freq > 0.0) {
float score = Similarity.tf(freq)*weight; // compute score
float score = similarity.tf(freq)*weight; // compute score
score *= Similarity.decodeNorm(norms[first.doc]); // normalize
results.collect(first.doc, score); // add to results
}

4
src/java/org/apache/lucene/search/PrefixQuery.java
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@ -90,8 +90,8 @@ public class PrefixQuery extends Query {
}
}
Scorer scorer(IndexReader reader) throws IOException {
return getQuery().scorer(reader);
Scorer scorer(IndexReader reader, Similarity similarity) throws IOException {
return getQuery().scorer(reader, similarity);
}
private BooleanQuery getQuery() throws IOException {

17
src/java/org/apache/lucene/search/Query.java
View File

@ -86,18 +86,19 @@ public abstract class Query implements java.io.Serializable
abstract void normalize(float norm);
// query evaluation
abstract Scorer scorer(IndexReader reader) throws IOException;
abstract Scorer scorer(IndexReader reader, Similarity similarity)
throws IOException;
void prepare(IndexReader reader) {}
static Scorer scorer(Query query, Searcher searcher, IndexReader reader)
throws IOException
{
query.prepare(reader);
float sum = query.sumOfSquaredWeights(searcher);
float norm = 1.0f / (float)Math.sqrt(sum);
query.normalize(norm);
return query.scorer(reader);
throws IOException {
Similarity similarity = searcher.getSimilarity();
query.prepare(reader);
float sum = query.sumOfSquaredWeights(searcher);
float norm = similarity.queryNorm(sum);
query.normalize(norm);
return query.scorer(reader, similarity);
}
/**

4
src/java/org/apache/lucene/search/RangeQuery.java
View File

@ -113,9 +113,9 @@ public class RangeQuery extends Query
}
}
Scorer scorer(IndexReader reader) throws IOException
Scorer scorer(IndexReader reader, Similarity similarity) throws IOException
{
return getQuery().scorer(reader);
return getQuery().scorer(reader, similarity);
}
private BooleanQuery getQuery() throws IOException

10
src/java/org/apache/lucene/search/Scorer.java
View File

@ -57,5 +57,15 @@ package org.apache.lucene.search;
import java.io.IOException;
abstract class Scorer {
private Similarity similarity;
protected Scorer(Similarity similarity) {
this.similarity = similarity;
}
public Similarity getSimilarity() {
return this.similarity;
}
abstract void score(HitCollector hc, int maxDoc) throws IOException;
}

23
src/java/org/apache/lucene/search/Searcher.java
View File

@ -63,9 +63,6 @@ import org.apache.lucene.index.IndexReader;
* Implements some common utility methods.
*/
public abstract class Searcher implements Searchable {
protected Similarity similarity;
/** Returns the documents matching <code>query</code>. */
public final Hits search(Query query) throws IOException {
return search(query, (Filter)null);
@ -91,12 +88,22 @@ public abstract class Searcher implements Searchable {
search(query, (Filter)null, results);
}
/**
* Sets the <code>Similarity</code> implementation to use.
/** The Similarity implementation used by this searcher. */
private Similarity similarity = Similarity.getDefault();
/** Expert: Set the Similarity implementation used by this Searcher.
*
* @param sim an instance of a class that implements <code>Similarity</code
* @see Similarity#setDefault(Similarity)
*/
public void setSimilarity(Similarity sim) {
similarity = sim;
public void setSimilarity(Similarity similarity) {
this.similarity = similarity;
}
/** Expert: Return the Similarity implementation used by this Searcher.
*
* <p>This defaults to the current value of {@link Similarity#getDefault()}.
*/
public Similarity getSimilarity() {
return this.similarity;
}
}

244
src/java/org/apache/lucene/search/Similarity.java
View File

@ -55,14 +55,73 @@ package org.apache.lucene.search;
*/
import java.io.IOException;
import java.util.Vector;
import org.apache.lucene.index.Term;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import org.apache.lucene.index.IndexReader;
import org.apache.lucene.index.IndexWriter;
/** Internal class used for scoring.
* <p>Public only so that the indexing code can compute and store the
* normalization byte for each document. */
/** Expert: Scoring API.
* <p>Subclasses implement search scoring.
*
* <p>The score of query <code>q</code> for document <code>d</code> is defined
* in terms of these methods as follows:
*
* <table cellpadding="0" cellspacing="0" border="0">
* <tr>
* <td valign="middle" align="right" rowspan="2">score(q,d) =<br></td>
* <td valign="middle" align="center">
* <big><big><big><big><big>&Sigma;</big></big></big></big></big></td>
* <td valign="middle"><small>
* {@link #tf(int) tf}(t in d) *
* {@link #idf(Term,Searcher) idf}(t) *
* {@link Field#getBoost getBoost}(t.field in d) *
* {@link #lengthNorm(String,int) lengthNorm}(t.field in d)
* </small></td>
* <td valign="middle" rowspan="2">&nbsp;*
* {@link #coord(int,int) coord}(q,d) *
* {@link #queryNorm(float) queryNorm}(q)
* </td>
* </tr>
* <tr>
* <td valign="top" align="right">
* <small>t in q</small>
* </td>
* </tr>
* </table>
*
* @see #setDefault(Similarity)
* @see IndexWriter#setSimilarity(Similarity)
* @see Searcher#setSimilarity(Similarity)
*/
public abstract class Similarity {
/** The Similarity implementation used by default. */
private static Similarity defaultImpl = new DefaultSimilarity();
/** Set the default Similarity implementation used by indexing and search
* code.
*
* @see Searcher#setSimilarity(Similarity)
* @see IndexWriter#setSimilarity(Similarity)
*/
public static void setDefault(Similarity similarity) {
Similarity.defaultImpl = similarity;
}
/** Return the default Similarity implementation used by indexing and search
* code.
*
* <p>This is initially an instance of {@link DefaultSimilarity}.
*
* @see Searcher#setSimilarity(Similarity)
* @see IndexWriter#setSimilarity(Similarity)
*/
public static Similarity getDefault() {
return Similarity.defaultImpl;
}
/** Cache of decoded bytes. */
private static final float[] NORM_TABLE = new float[256];
static {
@ -70,31 +129,6 @@ public abstract class Similarity {
NORM_TABLE[i] = byteToFloat((byte)i);
}
private static Similarity similarity;
private Similarity() {} // no public constructor
/**
* Sets the <code>Similarity</code> implementation to use.
*
* @param sim an instance of a class that implements <code>Similarity</code
*/
public static void setDefaultSimilarity(Similarity sim) {
similarity = sim;
}
/** Computes the normalization value for a document given the total number of
* terms contained in a field. These values are stored in an index and used
* by the search code.
*
* <p>The formula used is: <code>1.0f / Math.sqrt(numTerms)</code>
*
* @see Field#setBoost(float)
*/
public static float normalizeLength(int numTerms) {
return (float)(1.0 / Math.sqrt(numTerms));
}
/** Decodes a normalization factor stored in an index.
* @see #encodeNorm(float)
*/
@ -102,6 +136,41 @@ public abstract class Similarity {
return NORM_TABLE[b & 0xFF];
}
/** Computes the normalization value for a field given the total number of
* terms contained in a field. These values, together with field boosts, are
* stored in an index and multipled into scores for hits on each field by the
* search code.
*
* <p>Matches in longer fields are less precise, so implemenations of this
* method usually return smaller values when <code>numTokens</code> is large,
* and larger values when <code>numTokens</code> is small.
*
* <p>That these values are computed under {@link
* IndexWriter#addDocument(Document)} and stored then using
* {#encodeNorm(float)}. Thus they have limited precision, and documents
* must be re-indexed if this method is altered.
*
* @param fieldName the name of the field
* @param numTokens the total number of tokens contained in fields named
* <i>fieldName</i> of <i>doc</i>.
* @return a normalization factor for hits on this field of this document
*
* @see Field#setBoost(float)
*/
public abstract float lengthNorm(String fieldName, int numTokens);
/** Computes the normalization value for a query given the sum of the squared
* weights of each of the query terms. This value is then multipled into the
* weight of each query term.
*
* <p>This does not affect ranking, but rather just attempts to make scores
* from different queries comparable.
*
* @param sumOfSquaredWeights the sum of the squares of query term weights
* @return a normalization factor for query weights
*/
public abstract float queryNorm(float sumOfSquaredWeights);
/** Encodes a normalization factor for storage in an index.
*
* <p>The encoding uses a five-bit exponent and three-bit mantissa, thus
@ -151,25 +220,118 @@ public abstract class Similarity {
return (byte)((exponent << 3) | mantissa); // pack into a byte
}
static final float tf(int freq) {
return (float)Math.sqrt(freq);
/** Computes a score factor based on a term or phrase's frequency in a
* document. This value is multiplied by the {@link #idf(Term, Searcher)}
* factor for each term in the query and these products are then summed to
* form the initial score for a document.
*
* <p>Terms and phrases repeated in a document indicate the topic of the
* document, so implemenations of this method usually return larger values
* when <code>freq</code> is large, and smaller values when <code>freq</code>
* is small.
*
* <p>The default implementation calls {@link #tf(float)}.
*
* @param tf the frequency of a term within a document
* @return a score factor based on a term's within-document frequency
*/
public float tf(int freq) {
return tf((float)freq);
}
static final float tf(float freq) {
return (float)Math.sqrt(freq);
}
/** Computes the amount of a sloppy phrase match, based on an edit distance.
* This value is summed for each sloppy phrase match in a document to form
* the frequency that is passed to {@link #tf(float)}.
*
* <p>A phrase match with a small edit distance to a document passage more
* closely matches the document, so implemenations of this method usually
* return larger values when the edit distance is small and smaller values
* when it is large.
*
* @see PhraseQuery#setSlop(int)
* @param distance the edit distance of this sloppy phrase match
* @return the frequency increment for this match
*/
public abstract float sloppyFreq(int distance);
/** Computes a score factor based on a term or phrase's frequency in a
* document. This value is multiplied by the {@link #idf(Term, Searcher)}
* factor for each term in the query and these products are then summed to
* form the initial score for a document.
*
* <p>Terms and phrases repeated in a document indicate the topic of the
* document, so implemenations of this method usually return larger values
* when <code>freq</code> is large, and smaller values when <code>freq</code>
* is small.
*
* @param tf the frequency of a term within a document
* @return a score factor based on a term's within-document frequency
*/
public abstract float tf(float freq);
static final float idf(Term term, Searcher searcher) throws IOException {
// Use maxDoc() instead of numDocs() because its proportional to docFreq(),
// i.e., when one is inaccurate, so is the other, and in the same way.
/** Computes a score factor for a simple term.
*
* <p>The default implementation is:<pre>
* return idf(searcher.docFreq(term), searcher.maxDoc());
* </pre>
*
* Note that {@link Searcher#maxDoc()} is used instead of {@link
* IndexReader#numDocs()} because it is proportional to {@link
* Searcher#docFreq(Term)} , i.e., when one is inaccurate, so is the other,
* and in the same direction.
*
* @param term the term in question
* @param searcher the document collection being searched
* @return a score factor for the term
*/
public float idf(Term term, Searcher searcher) throws IOException {
return idf(searcher.docFreq(term), searcher.maxDoc());
}
static final float idf(int docFreq, int numDocs) {
return (float)(Math.log(numDocs/(double)(docFreq+1)) + 1.0);
/** Computes a score factor for a phrase.
*
* <p>The default implementation sums the {@link #idf(Term,Searcher)} factor
* for each term in the phrase.
*
* @param terms the vector of terms in the phrase
* @param searcher the document collection being searched
* @return a score factor for the phrase
*/
public float idf(Vector terms, Searcher searcher) throws IOException {
float idf = 0.0f;
for (int i = 0; i < terms.size(); i++) {
idf += idf((Term)terms.elementAt(i), searcher);
}
return idf;
}
/** Computes a score factor based on a term's document frequency (the number
* of documents which contain the term). This value is multiplied by the
* {@link #tf(int)} factor for each term in the query and these products are
* then summed to form the initial score for a document.
*
* <p>Terms that occur in fewer documents are better indicators of topic, so
* implemenations of this method usually return larger values for rare terms,
* and smaller values for common terms.
*
* @param docFreq the number of documents which contain the term
* @param numDocs the total number of documents in the collection
* @return a score factor based on the term's document frequency
*/
protected abstract float idf(int docFreq, int numDocs);
static final float coord(int overlap, int maxOverlap) {
return overlap / (float)maxOverlap;
}
/** Computes a score factor based on the fraction of all query terms that a
* document contains. This value is multiplied into scores.
*
* <p>The presence of a large portion of the query terms indicates a better
* match with the query, so implemenations of this method usually return
* larger values when the ratio between these parameters is large and smaller
* values when the ratio between them is small.
*
* @param overlap the number of query terms matched in the document
* @param maxOverlap the total number of terms in the query
* @return a score factor based on term overlap with the query
*/
public abstract float coord(int overlap, int maxOverlap);
}

10
src/java/org/apache/lucene/search/SloppyPhraseScorer.java
View File

@ -62,10 +62,10 @@ import org.apache.lucene.index.*;
final class SloppyPhraseScorer extends PhraseScorer {
private int slop;
SloppyPhraseScorer(TermPositions[] tps, int s, byte[] n, float w)
throws IOException {
super(tps, n, w);
slop = s;
SloppyPhraseScorer(TermPositions[] tps, Similarity similarity,
int slop, byte[] norms, float weight) throws IOException {
super(tps, similarity, norms, weight);
this.slop = slop;
}
protected final float phraseFreq() throws IOException {
@ -94,7 +94,7 @@ final class SloppyPhraseScorer extends PhraseScorer {
int matchLength = end - start;
if (matchLength <= slop)
freq += 1.0 / (matchLength + 1); // penalize longer matches
freq += getSimilarity().sloppyFreq(matchLength); // score match
if (pp.position > end)
end = pp.position;

7
src/java/org/apache/lucene/search/TermQuery.java
View File

@ -73,7 +73,7 @@ public class TermQuery extends Query {
}
final float sumOfSquaredWeights(Searcher searcher) throws IOException {
idf = Similarity.idf(term, searcher);
idf = searcher.getSimilarity().idf(term, searcher);
weight = idf * boost;
return weight * weight; // square term weights
}
@ -83,14 +83,15 @@ public class TermQuery extends Query {
weight *= idf; // factor from document
}
Scorer scorer(IndexReader reader)
Scorer scorer(IndexReader reader, Similarity similarity)
throws IOException {
TermDocs termDocs = reader.termDocs(term);
if (termDocs == null)
return null;
return new TermScorer(termDocs, reader.norms(term.field()), weight);
return new TermScorer(termDocs, similarity,
reader.norms(term.field()), weight);
}
/** Prints a user-readable version of this query. */

19
src/java/org/apache/lucene/search/TermScorer.java
View File

@ -63,21 +63,23 @@ final class TermScorer extends Scorer {
private float weight;
private int doc;
private final int[] docs = new int[128]; // buffered doc numbers
private final int[] freqs = new int[128]; // buffered term freqs
private final int[] docs = new int[32]; // buffered doc numbers
private final int[] freqs = new int[32]; // buffered term freqs
private int pointer;
private int pointerMax;
private static final int SCORE_CACHE_SIZE = 32;
private float[] scoreCache = new float[SCORE_CACHE_SIZE];
TermScorer(TermDocs td, byte[] n, float w) throws IOException {
termDocs = td;
norms = n;
weight = w;
TermScorer(TermDocs td, Similarity similarity, byte[] norms, float weight)
throws IOException {
super(similarity);
this.termDocs = td;
this.norms = norms;
this.weight = weight;
for (int i = 0; i < SCORE_CACHE_SIZE; i++)
scoreCache[i] = Similarity.tf(i) * weight;
scoreCache[i] = getSimilarity().tf(i) * weight;
pointerMax = termDocs.read(docs, freqs); // fill buffers
@ -91,12 +93,13 @@ final class TermScorer extends Scorer {
final void score(HitCollector c, final int end) throws IOException {
int d = doc; // cache doc in local
Similarity similarity = getSimilarity(); // cache sim in local
while (d < end) { // for docs in window
final int f = freqs[pointer];
float score = // compute tf(f)*weight
f < SCORE_CACHE_SIZE // check cache
? scoreCache[f] // cache hit
: Similarity.tf(f)*weight; // cache miss
: similarity.tf(f)*weight; // cache miss
score *= Similarity.decodeNorm(norms[d]); // normalize for field

4
src/test/org/apache/lucene/index/DocTest.java
View File

@ -59,6 +59,7 @@ import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.store.Directory;
import org.apache.lucene.document.Document;
import org.apache.lucene.search.Similarity;
import org.apache.lucene.demo.FileDocument;
import java.io.File;
@ -95,7 +96,8 @@ class DocTest {
throws Exception {
Directory directory = FSDirectory.getDirectory("test", false);
Analyzer analyzer = new SimpleAnalyzer();
DocumentWriter writer = new DocumentWriter(directory, analyzer, 1000);
DocumentWriter writer =
new DocumentWriter(directory, analyzer, Similarity.getDefault(), 1000);
File file = new File(fileName);
Document doc = FileDocument.Document(file);

2
src/test/org/apache/lucene/search/TestDocBoost.java
View File

@ -76,7 +76,7 @@ public class TestDocBoost extends TestCase {
super(name);
}
public static void test() throws Exception {
public void testDocBoost() throws Exception {
RAMDirectory store = new RAMDirectory();
IndexWriter writer = new IndexWriter(store, new SimpleAnalyzer(), true);

161
src/test/org/apache/lucene/search/TestSimilarity.java Normal file
View File

@ -0,0 +1,161 @@
package org.apache.lucene.search;
/* ====================================================================
* The Apache Software License, Version 1.1
*
* Copyright (c) 2001 The Apache Software Foundation. All rights
* reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in
* the documentation and/or other materials provided with the
* distribution.
*
* 3. The end-user documentation included with the redistribution,
* if any, must include the following acknowledgment:
* "This product includes software developed by the
* Apache Software Foundation (http://www.apache.org/)."
* Alternately, this acknowledgment may appear in the software itself,
* if and wherever such third-party acknowledgments normally appear.
*
* 4. The names "Apache" and "Apache Software Foundation" and
* "Apache Lucene" must not be used to endorse or promote products
* derived from this software without prior written permission. For
* written permission, please contact apache@apache.org.
*
* 5. Products derived from this software may not be called "Apache",
* "Apache Lucene", nor may "Apache" appear in their name, without
* prior written permission of the Apache Software Foundation.
*
* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
* SUCH DAMAGE.
* ====================================================================
*
* This software consists of voluntary contributions made by many
* individuals on behalf of the Apache Software Foundation. For more
* information on the Apache Software Foundation, please see
* <http://www.apache.org/>.
*/
import org.apache.lucene.index.Term;
import org.apache.lucene.index.IndexWriter;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.Hits;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.store.RAMDirectory;
import org.apache.lucene.analysis.SimpleAnalyzer;
import org.apache.lucene.document.Document;
import org.apache.lucene.document.Field;
import junit.framework.TestCase;
import java.util.Vector;
/** Similarity unit test.
*
* @author Doug Cutting
* @version $Revision$
*/
public class TestSimilarity extends TestCase {
public TestSimilarity(String name) {
super(name);
}
public static class SimpleSimilarity extends Similarity {
public float lengthNorm(String field, int numTerms) { return 1.0f; }
public float queryNorm(float sumOfSquaredWeights) { return 1.0f; }
public float tf(float freq) { return freq; }
public float sloppyFreq(int distance) { return 2.0f; }
public float idf(Vector terms, Searcher searcher) { return 1.0f; }
public float idf(int docFreq, int numDocs) { return 1.0f; }
public float coord(int overlap, int maxOverlap) { return 1.0f; }
}
public void testSimilarity() throws Exception {
RAMDirectory store = new RAMDirectory();
IndexWriter writer = new IndexWriter(store, new SimpleAnalyzer(), true);
writer.setSimilarity(new SimpleSimilarity());
Document d1 = new Document();
d1.add(Field.Text("field", "a c"));
Document d2 = new Document();
d2.add(Field.Text("field", "a b c"));
writer.addDocument(d1);
writer.addDocument(d2);
writer.optimize();
writer.close();
final float[] scores = new float[4];
Searcher searcher = new IndexSearcher(store);
searcher.setSimilarity(new SimpleSimilarity());
Term a = new Term("field", "a");
Term b = new Term("field", "b");
Term c = new Term("field", "c");
searcher.search
(new TermQuery(b),
new HitCollector() {
public final void collect(int doc, float score) {
assertTrue(score == 1.0f);
}
});
BooleanQuery bq = new BooleanQuery();
bq.add(new TermQuery(a), false, false);
bq.add(new TermQuery(b), false, false);
//System.out.println(bq.toString("field"));
searcher.search
(bq,
new HitCollector() {
public final void collect(int doc, float score) {
//System.out.println("Doc=" + doc + " score=" + score);
assertTrue(score == (float)doc+1);
}
});
PhraseQuery pq = new PhraseQuery();
pq.add(a);
pq.add(c);
//System.out.println(pq.toString("field"));
searcher.search
(pq,
new HitCollector() {
public final void collect(int doc, float score) {
//System.out.println("Doc=" + doc + " score=" + score);
assertTrue(score == 1.0f);
}
});
pq.setSlop(2);
//System.out.println(pq.toString("field"));
searcher.search
(pq,
new HitCollector() {
public final void collect(int doc, float score) {
//System.out.println("Doc=" + doc + " score=" + score);
assertTrue(score == 2.0f);
}
});
}
}