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Zend Framework
1.12
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Public Member Functions | |
| lengthNorm ($fieldName, $numTokens) | |
| Computes the normalization value for a field given the total number of terms contained in a field. | |
| queryNorm ($sumOfSquaredWeights) | |
| Computes the normalization value for a query given the sum of the squared weights of each of the query terms. | |
| tf ($freq) | |
| Computes a score factor based on a term or phrase's frequency in a document. | |
| sloppyFreq ($distance) | |
| Computes the amount of a sloppy phrase match, based on an edit distance. | |
| idf ($input, Zend_Search_Lucene_Interface $reader) | |
| Computes a score factor for a simple term or a phrase. | |
| idfFreq ($docFreq, $numDocs) | |
| Computes a score factor based on a term's document frequency (the number of documents which contain the term). | |
| coord ($overlap, $maxOverlap) | |
| Computes a score factor based on the fraction of all query terms that a document contains. | |
Static Public Member Functions | |
| static | setDefault (Zend_Search_Lucene_Search_Similarity $similarity) |
| Set the default Similarity implementation used by indexing and search code. | |
| static | getDefault () |
| Return the default Similarity implementation used by indexing and search code. | |
| static | decodeNorm ($byte) |
| Decodes a normalization factor stored in an index. | |
| static | encodeNorm ($f) |
| Encodes a normalization factor for storage in an index. | |
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abstract |
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 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.
overlap - the number of query terms matched in the document maxOverlap - the total number of terms in the query Returns a score factor based on term overlap with the query
| integer | $overlap | |
| integer | $maxOverlap |
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static |
Decodes a normalization factor stored in an index.
| integer | $byte |
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static |
Encodes a normalization factor for storage in an index.
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.
| float | $f |
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static |
Return the default Similarity implementation used by indexing and search code.
| idf | ( | $input, | |
| Zend_Search_Lucene_Interface | $reader | ||
| ) |
Computes a score factor for a simple term or a phrase.
The default implementation is: return idfFreq(searcher.docFreq(term), searcher.maxDoc());
input - the term in question or array of terms reader - reader the document collection being searched Returns a score factor for the term
| mixed | $input | |
| Zend_Search_Lucene_Interface | $reader |
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abstract |
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 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 implemenations of this method usually return larger values for rare terms, and smaller values for common terms.
docFreq - the number of documents which contain the term numDocs - the total number of documents in the collection Returns a score factor based on the term's document frequency
| integer | $docFreq | |
| integer | $numDocs |
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abstract |
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 implemenations of this method usually return smaller values when 'numTokens' is large, and larger values when 'numTokens' is small.
That these values are computed under 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.
fieldName - name of field numTokens - the total number of tokens contained in fields named 'fieldName' of 'doc'. Returns a normalization factor for hits on this field of this document
| string | $fieldName | |
| integer | $numTokens |
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abstract |
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.
sumOfSquaredWeights - the sum of the squares of query term weights Returns a normalization factor for query weights
| float | $sumOfSquaredWeights |
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static |
Set the default Similarity implementation used by indexing and search code.
| Zend_Search_Lucene_Search_Similarity | $similarity |
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abstract |
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 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.
distance - the edit distance of this sloppy phrase match Returns the frequency increment for this match
| integer | $distance |
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abstract |
Computes a score factor based on a term or phrase's frequency in a document.
This value is multiplied by the 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.
freq - the frequency of a term within a document Returns a score factor based on a term's within-document frequency
| float | $freq |
1.8.3