1.3.4.8.11 Comparison: Longest Common Phrase

The Longest Common Phrase comparison compares two String values and determines whether they might match by determining the number of words in the longest phrase that is common to both values, whether that phrase represents the whole or a part of the String value.

A 'phrase' is defined as a sequence of words, separated by spaces.

Use the Longest Common Phrase comparison to find matches in String values with multiple words where the order of words is important - for example when matching whole names.

The Longest Common Phrase comparison is effectively an order-sensitive version of Word Match Count. It may be used in match rules that are low down in the decision table in order to find and review possible matches that have similarity but which have failed to match using other rules, for example, due to a number of non-matching words.

This comparison supports the use of result bands.

The following table describes the configuration options:

Option	Type	Description	Default Value
Match No Data pairs?	Yes/No	This option determines the result of a comparison when it compares two No Data (Null, or containing only whitespace characters) values for an identifier. If set to No, the comparison will give a 'no data' result when comparing a No Data value against another No Data value. If set to Yes, the comparison will give a result of 0 when comparing a No Data value against another No Data value. A 'no data' result will only be returned if a No Data value is compared against a populated value.	No
Ignore case?	Yes/No	Sets whether or not to ignore case when comparing values.	Yes
Character error tolerance	Integer	This option specifies a number of character edits that are 'tolerated' when comparing words with each other. All words with a Character Edit Distance of less than or equal to the specified figure will be considered as the same. For example, if set to 1, the Longest Common Phrase between "95 Charnwood Court, Mile End, Parnham, Middlesex" and "95 Charwood Court, Mile End, Parnam, Middlesex" would be 7 words in length, as all words match each other considering this tolerance.	0
Ignore tolerance on numbers?	Yes/No	This option allows the Character error tolerance to be ignored for words that consist entirely of numerics. For example, if set to Yes, and using a Character error tolerance of 1, the Longest Common Phrase between "95 Charnwood Court, Mile End, Parnham, Middlesex" and "96 Charnwood Court, Mile End, Parnam, Middlesex" would be 6 words in length, because the numbers 95 and 96 would be considered as different, despite the fact that they only differ by a single character. If set to No, numbers will be treated like any other words, so in the example above, the Longest Common Phrase would be 7 words in length, as 95 and 96 would be considered as the same.	Yes
Treat tolerance value as percentage?	Yes/No	This allows the Character error tolerance to be treated as a percentage of the word length in characters. For example, to tolerate a single character error for every five characters in a word, a value of 20% should be used. This option may be useful to avoid treating short words as the same when they differ by a single character, but to retain the ability to be tolerant of typos in longer words - for example, to consider "Parnham" and "Parnam" as the same, but to treat "Bath" and "Batt" as different. If set to Yes, the Character error tolerance option should be entered as a maximum percentage of the number of characters in a word that you allow to be different, while still considering each word as the same. For example, if set to True, a Character error tolerance of 20% will mean "Parnam" and "Parnham" will be considered as the same, as they have an edit distance of 1, and a longer word length of 7 characters - meaning a character match percentage error of 14%, which is below the 20% threshold.  The values "Bath" and "Batt", however, will not considered as the same, as they have a character match percentage error of 25% (1 error in 4 characters). If set to No, the Character error tolerance option will be treated as a character edit tolerance between words.	No

Example

In this example, the Longest Common Phrase comparison is used to identify possible matches in customer names. The following options are specified:

• Match No Data pairs? = No

• Ignore case? = Yes

• Character error tolerance = 0

• Ignore tolerance on numbers? = No

• Treat tolerance value as percentage? = No

Example results

With the above configuration, the following table illustrates some comparison results:

Table 1-48 Example Results: Longest Common Phrase

Value A	Value B	Comparison Result
Mike Robert Davis	Robert Mike Davis	1
Mike Robert Davis	Robert Davis	2
Mike Roberts	Mike Robert Davis	1
Mike Robert Davis	Mike Davis	1
Ian Stanley James	Ian S James	1
Ian James	Ian James Smith	2
Ian James Smith	Ian James SMITH	3