| Lucy::Index::Similarity - phpMan
Lucy::Index::Similarity(3) User Contributed Perl Documentation Lucy::Index::Similarity(3)
NAME
Lucy::Index::Similarity - Judge how well a document matches a query.
SYNOPSIS
package MySimilarity;
sub length_norm { return 1.0 } # disable length normalization
package MyFullTextType;
use base qw( Lucy::Plan::FullTextType );
sub make_similarity { MySimilarity->new }
DESCRIPTION
After determining whether a document matches a given query, a score must be calculated
which indicates how well the document matches the query. The Similarity class is used to
judge how "similar" the query and the document are to each other; the closer the
resemblance, they higher the document scores.
The default implementation uses Lucene's modified cosine similarity measure. Subclasses
might tweak the existing algorithms, or might be used in conjunction with custom Query
subclasses to implement arbitrary scoring schemes.
Most of the methods operate on single fields, but some are used to combine scores from
multiple fields.
CONSTRUCTORS
new()
my $sim = Lucy::Index::Similarity->new;
Constructor. Takes no arguments.
METHODS
length_norm(num_tokens)
Dampen the scores of long documents.
After a field is broken up into terms at index-time, each term must be assigned a weight.
One of the factors in calculating this weight is the number of tokens that the original
field was broken into.
Typically, we assume that the more tokens in a field, the less important any one of them
is -- so that, e.g. 5 mentions of "Kafka" in a short article are given more heft than 5
mentions of "Kafka" in an entire book. The default implementation of length_norm
expresses this using an inverted square root.
However, the inverted square root has a tendency to reward very short fields highly, which
isn't always appropriate for fields you expect to have a lot of tokens on average.
INHERITANCE
Lucy::Index::Similarity isa Clownfish::Obj.
perl v5.20.2 2015-12-01 Lucy::Index::Similarity(3)
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