org.apache.lucene.search.similarities
Class MultiSimilarity
java.lang.Object
org.apache.lucene.search.similarities.Similarity
org.apache.lucene.search.similarities.MultiSimilarity
public class MultiSimilarity
- extends Similarity
Implements the CombSUM method for combining evidence from multiple
similarity values described in: Joseph A. Shaw, Edward A. Fox.
In Text REtrieval Conference (1993), pp. 243-252
- WARNING: This API is experimental and might change in incompatible ways in the next release.
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
sims
protected final Similarity[] sims
MultiSimilarity
public MultiSimilarity(Similarity[] sims)
computeNorm
public void computeNorm(FieldInvertState state,
Norm norm)
- Description copied from class:
Similarity
- Computes the normalization value for a field, given the accumulated
state of term processing for this field (see
FieldInvertState
).
Implementations should calculate a norm value based on the field
state and set that value to the given Norm
.
Matches in longer fields are less precise, so implementations of this
method usually set smaller values when state.getLength()
is large,
and larger values when state.getLength()
is small.
- Specified by:
computeNorm
in class Similarity
- Parameters:
state
- current processing state for this fieldnorm
- holds the computed norm value when this method returns
computeWeight
public Similarity.SimWeight computeWeight(float queryBoost,
CollectionStatistics collectionStats,
TermStatistics... termStats)
- Description copied from class:
Similarity
- Compute any collection-level weight (e.g. IDF, average document length, etc) needed for scoring a query.
- Specified by:
computeWeight
in class Similarity
- Parameters:
queryBoost
- the query-time boost.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.
- Returns:
- SimWeight object with the information this Similarity needs to score a query.
exactSimScorer
public Similarity.ExactSimScorer exactSimScorer(Similarity.SimWeight stats,
AtomicReaderContext context)
throws IOException
- Description copied from class:
Similarity
- Creates a new
Similarity.ExactSimScorer
to score matching documents from a segment of the inverted index.
- Specified by:
exactSimScorer
in class Similarity
- Parameters:
stats
- collection information from Similarity.computeWeight(float, CollectionStatistics, TermStatistics...)
context
- segment of the inverted index to be scored.
- Returns:
- ExactSimScorer for scoring documents across
context
- Throws:
IOException
sloppySimScorer
public Similarity.SloppySimScorer sloppySimScorer(Similarity.SimWeight stats,
AtomicReaderContext context)
throws IOException
- Description copied from class:
Similarity
- Creates a new
Similarity.SloppySimScorer
to score matching documents from a segment of the inverted index.
- Specified by:
sloppySimScorer
in class Similarity
- Parameters:
stats
- collection information from Similarity.computeWeight(float, CollectionStatistics, TermStatistics...)
context
- segment of the inverted index to be scored.
- Returns:
- SloppySimScorer for scoring documents across
context
- Throws:
IOException
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