public abstract class SimilarityBase extends Similarity
Similarity
that provides a simplified API for its
descendants. Subclasses are only required to implement the score(org.apache.lucene.search.similarities.BasicStats, float, float)
and toString()
methods. Implementing
explain(List, BasicStats, int, float, float)
is optional,
inasmuch as SimilarityBase already provides a basic explanation of the score
and the term frequency. However, implementers of a subclass are encouraged to
include as much detail about the scoring method as possible.
Note: multi-word queries such as phrase queries are scored in a different way than Lucene's default ranking algorithm: whereas it "fakes" an IDF value for the phrase as a whole (since it does not know it), this class instead scores phrases as a summation of the individual term scores.
Similarity.SimScorer, Similarity.SimWeight
Modifier and Type | Field and Description |
---|---|
protected boolean |
discountOverlaps
True if overlap tokens (tokens with a position of increment of zero) are
discounted from the document's length.
|
Constructor and Description |
---|
SimilarityBase()
Sole constructor.
|
Modifier and Type | Method and Description |
---|---|
long |
computeNorm(FieldInvertState state)
Encodes the document length in the same way as
TFIDFSimilarity . |
Similarity.SimWeight |
computeWeight(CollectionStatistics collectionStats,
TermStatistics... termStats)
Compute any collection-level weight (e.g.
|
protected float |
decodeNormValue(byte norm)
Decodes a normalization factor (document length) stored in an index.
|
protected byte |
encodeNormValue(float boost,
float length)
Encodes the length to a byte via SmallFloat.
|
protected Explanation |
explain(BasicStats stats,
int doc,
Explanation freq,
float docLen)
Explains the score.
|
protected void |
explain(List<Explanation> subExpls,
BasicStats stats,
int doc,
float freq,
float docLen)
Subclasses should implement this method to explain the score.
|
protected void |
fillBasicStats(BasicStats stats,
CollectionStatistics collectionStats,
TermStatistics termStats)
Fills all member fields defined in
BasicStats in stats . |
boolean |
getDiscountOverlaps()
Returns true if overlap tokens are discounted from the document's length.
|
static double |
log2(double x)
Returns the base two logarithm of
x . |
protected BasicStats |
newStats(String field)
Factory method to return a custom stats object
|
protected abstract float |
score(BasicStats stats,
float freq,
float docLen)
Scores the document
doc . |
void |
setDiscountOverlaps(boolean v)
Determines whether overlap tokens (Tokens with
0 position increment) are ignored when computing
norm.
|
Similarity.SimScorer |
simScorer(Similarity.SimWeight stats,
LeafReaderContext context)
Creates a new
Similarity.SimScorer to score matching documents from a segment of the inverted index. |
abstract String |
toString()
Subclasses must override this method to return the name of the Similarity
and preferably the values of parameters (if any) as well.
|
coord, queryNorm
protected boolean discountOverlaps
public SimilarityBase()
public void setDiscountOverlaps(boolean v)
computeNorm(org.apache.lucene.index.FieldInvertState)
public boolean getDiscountOverlaps()
setDiscountOverlaps(boolean)
public final Similarity.SimWeight computeWeight(CollectionStatistics collectionStats, TermStatistics... termStats)
Similarity
computeWeight
in class Similarity
collectionStats
- collection-level statistics, such as the number of tokens in the collection.termStats
- term-level statistics, such as the document frequency of a term across the collection.protected BasicStats newStats(String field)
protected void fillBasicStats(BasicStats stats, CollectionStatistics collectionStats, TermStatistics termStats)
BasicStats
in stats
.
Subclasses can override this method to fill additional stats.protected abstract float score(BasicStats stats, float freq, float docLen)
doc
.
Subclasses must apply their scoring formula in this class.
stats
- the corpus level statistics.freq
- the term frequency.docLen
- the document length.protected void explain(List<Explanation> subExpls, BasicStats stats, int doc, float freq, float docLen)
expl
already contains the score, the name of the class and the doc id, as well
as the term frequency and its explanation; subclasses can add additional
clauses to explain details of their scoring formulae.
The default implementation does nothing.
subExpls
- the list of details of the explanation to extendstats
- the corpus level statistics.doc
- the document id.freq
- the term frequency.docLen
- the document length.protected Explanation explain(BasicStats stats, int doc, Explanation freq, float docLen)
score(BasicStats, float, float)
method) and the explanation for the term frequency. Subclasses content with
this format may add additional details in
explain(List, BasicStats, int, float, float)
.stats
- the corpus level statistics.doc
- the document id.freq
- the term frequency and its explanation.docLen
- the document length.public Similarity.SimScorer simScorer(Similarity.SimWeight stats, LeafReaderContext context) throws IOException
Similarity
Similarity.SimScorer
to score matching documents from a segment of the inverted index.simScorer
in class Similarity
stats
- collection information from Similarity.computeWeight(CollectionStatistics, TermStatistics...)
context
- segment of the inverted index to be scored.context
IOException
- if there is a low-level I/O errorpublic abstract String toString()
public long computeNorm(FieldInvertState state)
TFIDFSimilarity
.computeNorm
in class Similarity
state
- current processing state for this fieldprotected float decodeNormValue(byte norm)
encodeNormValue(float,float)
protected byte encodeNormValue(float boost, float length)
public static double log2(double x)
x
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