Identity Resolution using NameSearch®Intelligent Search Technology's NameSearch product is a powerful identity resolution engine that enables you to find, link, search, match and group identities. This sophisticated software most effectively balances the competing requirements of increasing the quality of your searches while minimizing I/O expense and performance constraints.
One important aspect of NameSearch is the intelligent key and search range building algorithms. This facility is used for the indexing & retrieval of records regardless of variation caused by:
- Phonetics
- Transcription or keyboarding errors
- Nicknames
- Short forms
- Missing words
- Extra words
- Noise and sequence variations
- 65% of the population in the US has 1 out of 400 first names.
- 35% of the population has 1 out of 300 surnames.
- These are numbers taken from an analysis sample of over 3.2 million
first names and 2.5 million last names!
Traditional solutions for solving name variations only deal with phonetic errors. These solutions involved the standardization of easily confused sounds. For example, "PH"'s would be treated as "F"'s. Elaborate linguistic rules were generated to phonetically tokenize a name. These phonetically tokenized words served as the basis for name retrieval. In some instances these rules helped find names which were hard to spell, unfortunately, the distribution pattern of common names became even more distorted.
Discrepancies caused by phonetic errors account for 20-25% of all name variations. Intelligent Search Technology addresses problems due to phonetics by employing analysis routines to determine when phonetic tokenization should be applied. This enables NameSearch to overcome problems due to phonetics without the negative consequences incurred by other methods of name searching (i.e. wildcard, text searching, N-gram indexing or Soundex alone). No single algorithm or name matching system is the best for ALL naming data.
Instead, NameSearch leverages the best techniques including phonetics, transliteration, deterministic and probabilistic algorithms — prepackaged with an extensive pre-defined rule set. These rules can be used right out of the box or modified to meet your specific needs. This is done through the NameSearch Generation Shell.
The Generation Shell is a Graphical User Interface (GUI) designed for the modification and tuning of your NameSearch subroutines. The Shell allows you to adjust frequency and rule base tables, set various parameters, modify key building routines and test changes.
Rule based Expertise:
- Rule based expertise solves many classes of problems associated with name variations found in data. Names like Bill, William, Bob and Robert are used interchangeable to identify individuals, as well as numerous other nickname selections. The rule based expertise of the NameSearch Software can solve this, for example.
- The NameSearch rule base is also used to identify noise words. Noise words are elements in a name which do not help in the identification of a candidate. Examples of noise words are "Incorporated", "Corporation", "Limited", "Junior", "Senior", "Avenue" and "Street". Often there are times where elements in a name contribute to the identity but should be treated as less important. In these cases, the rule base does not treat them as noise words but recognizes that they are less significant. Some examples are "associate", "board", "international" and "services".
- The rule base also contains rules for handling common prefixes. For example, names like McDaniel are frequently confused with MacDaniel. Prefix recognition provides the function for handling this with ease.
- Another feature of the rule base is diminutive recognition. There are plenty of names which end in
a diminutive such as "ie" or "y". In these cases, it is useful to identify the root and apply the before mentioned rule. For example, you would want Bill, Billie and Billy to find William or Willie.
- These comparison routines can be used for the elimination of candidates from an on-line system,
providing the ability to tailor the information being displayed. This is especially useful for systems containing more than 10 million records.
- In addition, the comparison routines form the basis behind batch utilities, such as a merge/purge application. These comparison routines enable systems to make decisions without human intervention.
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