package org.apache.lucene.search;
/**
* Copyright 2004 The Apache Software Foundation
*
* Licensed 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.
*/
import java.io.IOException;
import java.util.Collection;
import java.util.Iterator;
import org.apache.lucene.index.Term;
import org.apache.lucene.index.IndexReader; // for javadoc
import org.apache.lucene.index.IndexWriter; // for javadoc
import org.apache.lucene.document.Field; // for javadoc
/** 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>Σ</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"> *
* {@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 {
for (int i = 0; i < 256; i++)
NORM_TABLE[i] = byteToFloat((byte)i);
}
/** Decodes a normalization factor stored in an index.
* @see #encodeNorm(float)
*/
public static float decodeNorm(byte b) {
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
* representing values from around 7x10^9 to 2x10^-9 with about one
* significant decimal digit of accuracy. Zero is also represented.
* Negative numbers are rounded up to zero. Values too large to represent
* are rounded down to the largest representable value. Positive values too
* small to represent are rounded up to the smallest positive representable
* value.
*
* @see Field#setBoost(float)
*/
public static byte encodeNorm(float f) {
return floatToByte(f);
}
private static float byteToFloat(byte b) {
if (b == 0) // zero is a special case
return 0.0f;
int mantissa = b & 7;
int exponent = (b >> 3) & 31;
int bits = ((exponent+(63-15)) << 24) | (mantissa << 21);
return Float.intBitsToFloat(bits);
}
private static byte floatToByte(float f) {
if (f < 0.0f) // round negatives up to zero
f = 0.0f;
if (f == 0.0f) // zero is a special case
return 0;
int bits = Float.floatToIntBits(f); // parse float into parts
int mantissa = (bits & 0xffffff) >> 21;
int exponent = (((bits >> 24) & 0x7f) - 63) + 15;
if (exponent > 31) { // overflow: use max value
exponent = 31;
mantissa = 7;
}
if (exponent < 0) { // underflow: use min value
exponent = 0;
mantissa = 1;
}
return (byte)((exponent << 3) | mantissa); // pack into a byte
}
/** 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 implementations 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 freq 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);
}
/** 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 implementations 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 freq 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);
/** 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());
}
/** 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 terms in the phrase
* @param searcher the document collection being searched
* @return a score factor for the phrase
*/
public float idf(Collection terms, Searcher searcher) throws IOException {
float idf = 0.0f;
Iterator i = terms.iterator();
while (i.hasNext()) {
idf += idf((Term)i.next(), 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
*/
public abstract float idf(int docFreq, int numDocs);
/** 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);
}
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