Type Parameters:: E - the type of the elements being matched.

All Known Implementing Classes:: MultiMatcher.Default

public interface MultiMatcher<E>

Logic for bidirectionally and exclusively linking all matching elements from two collections according to equality and/or sufficient similarity.

Exclusviely means each element in both collections can at most be linked with one element from the other collection. Bidirectionally means the link between two elements always has two directions. If element A is linked to element B, element B is inherently linked to element A as well.

Equality and similarity are defined by Equalator and Similator functions that can be passed at creation time. All values controlling the matching algorithm can be optionally configured in the factory class if the default configuration is not desired. Additionally, a callback function for deciding found matches with questionable similarity can be injected.

This is a powerful general purpose means of building associations of two sets of similar but not equal elements.
A very simple use case is the formal recognition of a changed table column structure (for which this class was originally developed).

For example given the following two hypothetical definitions (old and new) of column names:

Old:

Name
Firstname
Age
Address
Freetext
Email
OtherAddress

and

New:

firstname
lastname
age
emailAddress
postalAddress
noteLink
newColumn1
someMiscAddress

When using a case insensitive modified Levenshtein Similator (see Levenshtein.substringSimilarity(java.lang.String, java.lang.String)) the algorithm produces the following associations:

 firstname       -1.00- Firstname
 lastname        -0.75- Name
 age             -1.00- Age
 emailAddress    -0.71- Email
 postalAddress   -0.77- Address
 noteLink        [new]
 newColumn1      [new]
 someMiscAddress -0.56- OtherAddress
                      X Freetext

Nested Class Summary

Nested Classes

Modifier and Type Interface Description

static class MultiMatcher.Default<E>

Method Summary

Modifier and Type	Method	Description
`static double`	`defaultNoiseFactor()`
`static double`	`defaultSimilarityThreshold()`
`static double`	`defaultSingletonPrecedenceBonus()`
`static double`	`defaultSingletonPrecedenceThreshold()`
`Equalator<? super E>`	`equalator()`
`MultiMatch<E>`	`match(XGettingCollection<? extends E> source, XGettingCollection<? extends E> target)`
`static <E> MultiMatcher<E>`	`New()`
`double`	`noiseFactor()`
`MultiMatcher<E>`	`setEqualator(Equalator<? super E> equalator)`
`MultiMatcher<E>`	`setNoisefactor(double noiseFactor)`
`MultiMatcher<E>`	`setSimilarityThreshold(double similarityThreshold)`
`MultiMatcher<E>`	`setSimilator(Similator<? super E> similator)`
`MultiMatcher<E>`	`setSingletonPrecedenceBonus(double singletonPrecedenceBonus)`
`MultiMatcher<E>`	`setSingletonPrecedenceThreshold(double singletonPrecedenceThreshold)`
`MultiMatcher<E>`	`setValidator(MatchValidator<? super E> validator)`
`double`	`similarityThreshold()`
`Similator<? super E>`	`similator()`
`double`	`singletonPrecedenceBonus()`
`double`	`singletonPrecedenceThreshold()`	This is a measure of how "eager" the algorithm is to find as many matches as possible.
`MatchValidator<? super E>`	`validator()`

Method Details
- similarityThreshold
  
  double similarityThreshold()
- singletonPrecedenceThreshold
  
  double singletonPrecedenceThreshold()
  
  This is a measure of how "eager" the algorithm is to find as many matches as possible. The lower this threshold is, the more "single potential match" items will be preferred over actually better matching pairs just to not leave them unmatched. To deactivate this special casing, set the threshold to 1.0, meaning only items that fit perfectly anyway take precedence over others.
  
  Returns:
  
  the singleton precedence threshold
- singletonPrecedenceBonus
  
  double singletonPrecedenceBonus()
- noiseFactor
  
  double noiseFactor()
- equalator
  
  Equalator<? super E> equalator()
- similator
  
  Similator<? super E> similator()
- validator
  
  MatchValidator<? super E> validator()
- setSimilarityThreshold
  
  MultiMatcher<E> setSimilarityThreshold(double similarityThreshold)
- setSingletonPrecedenceThreshold
  
  MultiMatcher<E> setSingletonPrecedenceThreshold(double singletonPrecedenceThreshold)
- setSingletonPrecedenceBonus
  
  MultiMatcher<E> setSingletonPrecedenceBonus(double singletonPrecedenceBonus)
- setNoisefactor
  
  MultiMatcher<E> setNoisefactor(double noiseFactor)
- setSimilator
  
  MultiMatcher<E> setSimilator(Similator<? super E> similator)
- setEqualator
  
  MultiMatcher<E> setEqualator(Equalator<? super E> equalator)
- setValidator
  
  MultiMatcher<E> setValidator(MatchValidator<? super E> validator)
- match
  
  MultiMatch<E> match(XGettingCollection<? extends E> source, XGettingCollection<? extends E> target)
- defaultSimilarityThreshold
  
  static double defaultSimilarityThreshold()
- defaultSingletonPrecedenceThreshold
  
  static double defaultSingletonPrecedenceThreshold()
- defaultSingletonPrecedenceBonus
  
  static double defaultSingletonPrecedenceBonus()
- defaultNoiseFactor
  
  static double defaultNoiseFactor()
- New
  
  static <E> MultiMatcher<E> New()

Interface MultiMatcher<E>

Nested Class Summary

Method Summary

Method Details