File	Doc	Category	Size	Date	Package
Similarity.java	API Doc	Apache Lucene 2.1.0	21028	Wed Feb 14 10:46:40 GMT 2007	org.apache.lucene.search

Similarity

• java.lang.Object

Fields Summary
private static Similarity	defaultImpl The Similarity implementation used by default.
private static final float[]	NORM_TABLE Cache of decoded bytes.

Constructors Summary

Methods Summary
public abstract float	coord(int overlap, int maxOverlap) Computes a score factor based on the fraction of all query terms that a document contains. This value is multiplied into scores. The presence of a large portion of the query terms indicates a better match with the query, so implementations 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 static float	decodeNorm(byte b) Decodes a normalization factor stored in an index. see #encodeNorm(float) for (int i = 0; i < 256; i++) NORM_TABLE[i] = SmallFloat.byte315ToFloat((byte)i); return NORM_TABLE[b & 0xFF]; // & 0xFF maps negative bytes to positive above 127
public static byte	encodeNorm(float f) Encodes a normalization factor for storage in an index. The encoding uses a three-bit mantissa, a five-bit exponent, and the zero-exponent point at 15, 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 org.apache.lucene.document.Field#setBoost(float) see SmallFloat return SmallFloat.floatToByte315(f);
public static org.apache.lucene.search.Similarity	getDefault() Return the default Similarity implementation used by indexing and search code. This is initially an instance of {@link DefaultSimilarity}. see Searcher#setSimilarity(Similarity) see IndexWriter#setSimilarity(Similarity) return Similarity.defaultImpl;
public static float[]	getNormDecoder() Returns a table for decoding normalization bytes. see #encodeNorm(float) return NORM_TABLE;
public float	idf(org.apache.lucene.index.Term term, org.apache.lucene.search.Searcher searcher) Computes a score factor for a simple term. The default implementation is: return idf(searcher.docFreq(term), searcher.maxDoc()); 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 return idf(searcher.docFreq(term), searcher.maxDoc());
public float	idf(java.util.Collection terms, org.apache.lucene.search.Searcher searcher) Computes a score factor for a phrase. 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 float idf = 0.0f; Iterator i = terms.iterator(); while (i.hasNext()) { idf += idf((Term)i.next(), searcher); } return idf;
public abstract float	idf(int docFreq, int numDocs) 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. Terms that occur in fewer documents are better indicators of topic, so implementations 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	lengthNorm(java.lang.String fieldName, int numTokens) 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. Matches in longer fields are less precise, so implementations of this method usually return smaller values when numTokens is large, and larger values when numTokens is small. That these values are computed under {@link IndexWriter#addDocument(org.apache.lucene.document.Document)} and stored then using {@link #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 fieldName of doc. return a normalization factor for hits on this field of this document see org.apache.lucene.document.Field#setBoost(float)
public abstract float	queryNorm(float sumOfSquaredWeights) 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. 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 static void	setDefault(org.apache.lucene.search.Similarity similarity) Set the default Similarity implementation used by indexing and search code. see Searcher#setSimilarity(Similarity) see IndexWriter#setSimilarity(Similarity) Similarity.defaultImpl = similarity;
public abstract float	sloppyFreq(int distance) 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)}. 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	tf(float 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. Terms and phrases repeated in a document indicate the topic of the document, so implementations of this method usually return larger values when freq is large, and smaller values when freq 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 float	tf(int 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. Terms and phrases repeated in a document indicate the topic of the document, so implementations of this method usually return larger values when freq is large, and smaller values when freq is small. 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 return tf((float)freq);