Tutorial:Matchcodes

Overview

Matchcodes are sets of rules that tell MatchUp Object which data fields to consider when determining if two records are duplicates. MatchUp Object uses the matchcode to construct a "match key," a simplified string of characters that represents the information within the record, enough to determine if the given records is unique or a duplicate.

The topics in this section will go into detail on matchcode properties and usages. For information on how to use the Matchcode Editor, see the Matchcode Editor page.

Component Combinations

Every matchcode is composed of one or more possible combinations of components. These represent different possible situations in which this matchcode will detect a match between two records. A match found using any one of the combinations in a matchcode is considered a match. Programmers may think in terms of a series of OR conditions. Satisfying any one of them is considered a positive result.

MatchUp allows up to 16 different combinations of components per matchcode.

A good example of combinations would be a matchcode designed to catch last names as well as either street addresses or post office box addresses.

• Condition #1: ZIP/PC, Last Name, Street Number, Street Name
• Condition #2: ZIP/PC, Last Name, PO Box

Such a matchcode might look like this:

Component	Size	1	2
ZIP/PC	5	X	X
Last Name	5	X	X
Street #	4	X
Street Name	4	X
PO Box	10		X

Columns 3 through 16 have been omitted for the sake of clarity. The trick to understanding this table is to look at the vertical columns of X’s. For example, looking at column 1, there are X’s in ZIP/PC, Last Name, Street #, and Street Name, indicating the goal of condition #1 exactly. In column 2 are X’s in ZIP/PC, Last Name, and PO Box, matching condition #2.

For a more advanced example:

Component	Size	1	2	3	4
ZIP/PC	5	X	X	X	X
Last Name	5	X	X
Company	10			X	X
Street #	4	X		X
Street Name	4	X		X
PO Box	10		X		X

This matchcode produced matches under the following 4 conditions:

• Condition #1: ZIP/PC, Last Name, Street Number, Street Name
• Condition #2: ZIP/PC, Last Name, PO Box
• Condition #3: ZIP/PC, Company, Street Number, Street Name
• Condition #4: ZIP/PC, Company, PO Box

This matchcode could be used on a mailing list containing a mixture of both personal and company names and either street or PO Box™ addresses.

First Component Restrictions

The first component in any matchcode is special. This is the component that is used for clustering records, an essential element in efficient deduping. Thus, this component has certain restrictions placed on it. The Matchcode Editor enforces these restrictions automatically.

1. It must appear in every combination.
2. It cannot use the following types of Fuzzy matching: Containment; Frequency; Fast Near; Frequency Near; Accurate Near. All others are allowed.
3. It cannot use Initial Only matching.
4. It cannot use One Blank Field matching.
5. It cannot use Swap Matching.

Blank Field Matching

This needs a special discussion, as its importance is often overlooked. If this property is on, then the absence of data in both records would indicate a match. If this property is off, then two records with missing data, but matching in every other way, will not match. It would be reasonable to wonder if you would not want this behavior. However, it is undesirable in certain situations.

Take the following matchcode (paying attention to the Blank column):

Component	Size	Blank	1	2
Component	Size	Blank	1	2
ZIP/PC	5	Yes	X	X
Last Name	5	Yes	X	X
Street #	4	Yes	X
Street Name	4	Yes	X
PO Box	10	Yes		X

As described above, this produces the following combinations:

• Condition #1: ZIP/PC, Last Name, Street Number, Street Name
• Condition #2: ZIP/PC, Last Name, PO Box

For this example, take the following records:

Name:           Joe Smith           Suzi Smith
Address:        326 Main Street     405 Main St
City/State/PC:  Pembroke, MA 02066  Pembroke, MA 02066

The following matchcode keys would be generated:

Cond#	ZIP/PC	Last Name	Street #	Street Name	PO Box
1	02066	SMITH	326	MAIN
2	02066	SMITH	405	MAIN

According to these matchcode keys, it is clear that these two records do not satisfy condition #1. But because blank field matching is selected, they do satisfy condition #2. The Zip/PC, Last Name, and PO Box are exactly the same. Therefore, the two records do match.

Obviously, this is not the correct result. Making one change to the matchcode:

Component	Size	Blank	1	2
ZIP/PC	5	Yes	X	X
Last Name	5	Yes	X	X
Street #	4	Yes	X
Street Name	4	Yes	X
PO Box	10	No		X

The same comparison is done for combination #2, but the match is disallowed this time because the matchcode now indicates that missing (blank) information is not allowed to figure in the matching condition.

Looking at another example (using the same matchcode):

Name:           Joe Smith           Suzi Smith
Address:        PO Box 123          PO Box 456
City/State/PC:  Pembroke, MA 02066  Pembroke, MA 02066

This pairing produces the following matchcode keys:

Cond#	ZIP/PC	Last Name	Street #	Street Name	PO Box
1	02066	SMITH			123
2	02066	SMITH			456

This record has the same problem as before, but this time combination #1 is the cause.

An even better matchcode would be:

Component	Size	Blank	1	2
ZIP/PC	5	Yes	X	X
Last Name	5	Yes	X	X
Street #	4	No	X
Street Name	4	No	X
PO Box	10	No		X

This is one matchcode that works well. There is one more possible tweak, however:

Turn on Both Blank Fields for the Street # component. Occasionally, MatchUp Object may encounter records such as:

Name:           Joe Notarangello    Suzi Notarangello
Address:        Oceanfront Estates  Oceanfront Est.
City/State/PC:  Pembroke, MA 02066  Pembroke, MA 02066

This reflects a trend in up-scale neighborhoods, where neither street address has a Street # component, though it is very likely these records should match.

So this new, improved matchcode will account for these situations:

Component	Size	Blank	1	2
ZIP/PC	5	Yes	X	X
Last Name	5	Yes	X	X
Street #	4	Yes	X
Street Name	4	No	X
PO Box	10	No		X

Matchcode Mapping

Matchcodes deal with the abstract. The components in a matchcode represent specific types of data, but they aren't directly linked to the fields in databases. Mapping creates the link between the data and the matchcode.

For example, take the following matchcode:

Component	Size	Fuzzy	1
ZIP5	5	No	X
Last Name	5	No	X
First Name	5	No	X
Company	10	No	X

Add a database that contains the following fields:

NAME:     Contains full names ("Mr. John Smith").
COMPANY:  Contains company names ("Melissa Data")
ADD1:     Contains first (primary) address line ("22382 Avenida Empresa").
ADD2:     Contains second (secondary) address line ("Suite 34").
CSZ:      Contains City/Sate/Zip ("Rancho Santa Margarita, CA 92688").

An application must create a link between a database's fields (Name, Company, Add1, Add2 and CSZ) and the matchcode components (Zip5, Last Name, First Name, Company).

With the example above, it may appear that the application will have to contain extensive splitting routines. This is not the case. All that is necessary is to tell MatchUp what type of data is in a specific field and the format of that data.

In the example above, an application would use the following matchcode mapping:

Component	Database Field	Matchcode Mapping
ZIP5	CSZ	CityStZip
Last Name	NAME	FullName
First Name	NAME	FullName
Company	COMPANY	Company

This mapping tells MatchUp that the 5-digit ZIP Code information is in a field named "CSZ" which is described as a field containing city, state, and ZIP Code information. The Last Name can be found in a field called "NAME" and is described as a full name field (which is a full name sequenced: Pre, FN, MN, LN, Suf).

Matchcode mappings follow five rules:

1. For every Matchcode Component, the application must specify a mapping. The only exception is described in rule 2.
2. Actual Address components names (such as Street Number, Street Pre-Directional, Street Name, Street Suffix, Street Post-Directional, PO Box, and Street Secondary) are not listed for mapping purposes. Instead, the names Address Line 1, Address Line 2, and Address Line 3 are used. The example below used four address components in the matchcode (Street #, Street Name, Street Secondary, PO Box). However, it only used two address lines.
3. If a matchcode uses any address components, Address Lines 1-3 will be listed after all other components regardless of where the address component appears in the matchcode. In the following example, the address components are listed before company in the matchcode, but Address Lines 1-2 are listed at the end (after company).
4. If a matchcode uses address components, Address Lines 1-3 will require at least one line to be mapped, but not all. If a database only has one address field, an application will only need to map Address 1 to that field. All other components must be mapped.
5. Address Lines should be mapped from the top down (Address Line1, then 2, then 3).

Enhancing the matchcode in the previous example:

Component	Size	Fuzzy	1	2
ZIP5	5	No	X
Last Name	5	No	X
First Name	5	No	X
Street #	5	No	X
Street Name	5	No	X
Street Secondary	12	No	X
PO Box	10	No		X
Company	10	No	X	X

Again, MatchUp doesn't use the individual address components. They are replaced with Address 1, Address 2, and Address 3. So, the application would use the following Matchcode Mapping:

Matchcode Component	Database Field	Matchcode Mapping
ZIP9	CSZ	CityStZip
Last Name	NAME	FullName
First Name	NAME	FullName
Company	COMPANY	Company
Address Line 1	ADD1	Address
Address Line 2	ADD2	Address
Address Line 3	(none)

Note on Rule #1

If a database does not contain a field for information called for by a component in a matchcode, such as company field in the above example, then that matchcode should not be used to dedupe that database.

Use a different matchcode or modify an existing matchcode, as outlined later in this chapter.

However, if a matchcode calls for last name, for example, and the database only has full name, then simply map the full name field to the last name and MatchUp Object will handle parsing the field.

Optimizing Matchcodes

Some matchcodes process much faster than others in spite of the fact that they detect the same matches. This section will assist in creating the most efficient matchcodes. This discussion is included so developers can better understand why certain things are done while optimizing, as well as what can be done to make the optimizer work more effectively.

Optimizing can make a significant difference in processing speed. 58-hour runs have been reduced to four hours simply by optimizing the matchcode.

It is important, however, that the developer verifies that a matchcode works in the intended way before attempting any optimizations. If a matchcode is not functioning properly, these optimizations will not help, and could quite possibly make the situation worse.

Component Sequence

As discussed in the previous section, the first component of a matchcode has certain restrictions:

• It must be used in every combination.
• It cannot use certain types of Fuzzy Matching: Containment; Frequency; Fast Near; Frequency Near, or Accurate Near (other types are okay, though).
• It cannot use Initial Only matching.
• It cannot use One Blank Field matching.
• It cannot use Swap matching.

If the matchcode's second component also follows these conditions, MatchUp Object will incorporate it into its clustering scheme (see page 3 for more information on clustering). Additional components, if they follow in sequence (third, fourth, and so on), will be used if they, too, satisfy these conditions. Incorporating a component into a cluster greatly reduces the number of comparisons MatchUp Object has to perform which, in turn, speeds up your processing.

This is a simple example of optimization:

Component	Size	Fuzzy	Blank	1	2
ZIP/PC	5	No	Yes	X	X
Street #	5	No	Yes	X
Street Name	5	No	No	X
PO Box	10	No	No		X
Last Name	5	No	Yes	X	X

As shown here, MatchUp Object will only cluster by ZIP/PC. But note that the last component satisfies all the conditions listed earlier.

Component	Size	Fuzzy	Blank	1	2
ZIP/PC	5	No	Yes	X	X
Last Name	5	No	Yes	X	X
Street #	5	No	Yes	X
Street Name	5	No	No	X
PO Box	10	No	No		X

This simple optimization will produce significant improvements in speed. The Matchcode Optimizer will always perform this optimization.

Fuzzy Algorithms

Fuzzy algorithms fall into two categories: early matching and late matching.

Early matching algorithms are algorithms where a string is transformed into a (usually shorter) representation and comparisons are performed on this result. In MatchUp, these transformations are performed during key generation (the BuildKey function in each interface), which means that the early matching algorithms pay a speed penalty once per record: as each record’s key is built.

Late matching algorithms are actual comparison algorithms. Usually, one string is shifted in one direction or another, and often a matrix of some sort is used to derive a result. These transformations are performed during key comparison. As a result, late matching algorithms pay a speed penalty every time a record is compared to another record. This may happen several hundred times per record.

Obviously, late matching is much slower than early matching. If a particular matchcode is very slow, changing to a faster fuzzy matching algorithm may improve the speed. Often, a faster algorithm will give nearly the same results, but it is a good idea to test any such change before processing live data.

The fuzzy algorithms, ranked from slowest to fastest:

Algorithm	Late or Early	Speed (10 = Fastest)
Algorithm Late or Early Speed (10 = fastest)
Accurate Near	Late	1
Fast Near	Late	3
Containment	Late	4
Frequency Near	Late	4
Frequency	Late	6
Phonetex	Early	7
Soundex	Early	8
Vowels Only	Early	9
Numerics Only	Early	9
Consonants Only	Early	9
Alphas Only	Early	9
Exact	N/A	10

The speed values are only rough estimates. All the advanced algorithms are Speed = 1.

Another benefit of using a faster fuzzy algorithm is that an application may be able to exploit the component sequence optimization shown earlier. All of the early matching algorithms satisfy the restrictions for first components.

The Matchcode Optimizer will not perform this optimization as it can have a significant impact on matching results.

Unnecessary Components

Components that are not used in any combinations (in other words, they have no X's in columns 1 through 16) are a sign of poor matchcode design.

Take the following matchcode:

Component	Size	Fuzzy	Blank	1	2
ZIP5	5	No	Yes	X	X
Last Name	5	No	Yes	X	X
First Name	5	No	Yes
Street #	5	No	Yes	X
Street Name	5	No	No	X
PO Box	10	No	No		X

First name is not being used in any combination. Perhaps it was used in a combination that has since been removed from this matchcode, but is no longer necessary.

Unnecessary Combinations

Take the following matchcode:

Component	Size	Fuzzy	Blank	1	2	3	4
ZIP5	5	No	Yes	X	X	X	X
Last Name	5	No	Yes	X	X	X	X
First Name	5	No	Yes
Street #	5	No	Yes	X		X
Street Name	5	No	No	X		X
PO Box	10	No	No		X		X

Here are the four conditions for matching:

Condition #1  ZIP/PC  Last Name  First Name  Street #  Street Name
Condition #2  ZIP/PC  Last Name  First Name                         PO Box
Condition #3  ZIP/PC  Last Name              Street #  Street Name
Condition #4  ZIP/PC  Last Name                                     PO Box

There is no match that will be detected by condition #1 that would not be detected by condition #3. Similarly, matches found by condition #2 will always be found by condition #4. In other words, condition 3 is a subset of condition 1, and condition 2 is a subset of condition 4. Subsets are rarely desirable.

So either conditions 1 and 2 aren’t needed or conditions 3 and 4 were a mistake. If conditions 1 and 2 are eliminated, the First Name component should also be removed, as it will not be needed.

Swap Matching Uses

Swap matching is used to catch matches when two fields are flipped around. The most common occasion is catching the "John Smith" and "Smith John" records. But there are other uses:

Comparing Household Records

When there are two or three first or full names per record, a list provider may claim that every record is always "husband, wife, then children," but records will read wife then child and husband:

In the above example, select Either component can match for Swap Pairs A, B, and C

Comparing up to Three Address Lines

Although the address splitter works well in the US and Canada, some European countries can cause problems. A typical Euro-Matchcode will not use street split components and look at three address lines instead. The swap matching ensures that every address line is compared with every other address line.

Again, select Either component can match for Swap Pairs A, B, and C.

Don’t always discard the street split component matchcodes because you are working with a foreign database. Sometimes the street splitter will yield usable results. Therefore, a combination of approaches will often work.