Details about the Go!Scan scoring
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In the case were no filter is set, the default values apply:
Threshold: 50% (100% in case of Exact match required)
Weighting: First name 33%, Last name 66%
Date of birth: Only year of birth is compared
All records types are returned (SIP, SIE, PEP, and associates RCAs) active or not, deceased or not, etc.
Before any score computation, a boolean filter is applied to the search. You will find more details about all the options of this filter here: Go!Scan post-filtering.
When executing a search on ElasticSearch we will execute a fuzzy search. This work by generating alternative versions of the search input, for instance a search against the name “James” will in fact search for any record of one of the following form: “Jmes”, “ames”, “Jmaes”, “Jams”, etc. We generate for each words up to 50 variations. The variations depends on the size of the string using the following logic: between 0 and 2 characters no variation created, between 3 and 5 only one edit is allowed, for more than 6 characters only two edits are allowed. One edit match one integer using the Levenshtein distance.
This variations are used to search against all the names fields present in the records in any order. We use multiple nested search queries to boost candidates having a match in the correct category (for instance if the first name James matches a last name Jakes it will have a lower sort score than if it matches a first name Jakes).
The most records matches the input, the better the order score will be. More details about the sort score can be found here: https://www.compose.com/articles/how-scoring-works-in-elasticsearch/.
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enc_U2FsdGVkX19SQB64vNWfeC9d3UzYsH5Pq6JlgD0ViOQTKJcSBwLatcGP+7sxFA3zl7wxcOEEgkAIijgXbVecIA==_enc enc_U2FsdGVkX1+drjE16Mz6QPDDIxV1euyDJ+Kns1zLEqWqT8S74lUNtzrdi/l6ZFQ/hzJa9XfwtHhWNIA7NylLhw==_enc
The Record contains multiple names, for instance the Record first name could be the single string "Brigitte"
and the Record last name could be the list of strings ["Macron", "Trogneux"]
.
For the Query with first name “Brigite” and last name “Macon”, we do the following.
If exact date of birth is required, only will be returned the record:
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enc_U2FsdGVkX1+nTANxLmqW1plLR9d2wtcX8pHvUlfxo66m4LfciPEXG9bEzXzddIrMGliv+xexPuHOeqKLGkaKO+7Ii7dMZkGX50nzHivqafmtuxbtGEyNb4w9HP/lMUShttXbNRUOp0tvGjWWEDyKjA==_enc
Description | Penalty |
---|---|
Full alignment of all names in a single record variation | 0% |
Full alignment of all names but across multiple record variations | 0% |
Reverted first name and middle name | 1% |
Shuffled names (all found but all in different categories) | 2% |
All names are present but for instance first name and last name are both in the first name category | 3% |
Some names are not found but the record also don’t have this name type. For instance first name was not matched, but the record doesn’t have a first name registered. | 4% |
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Description | Penalty |
---|---|
Requested a match in a category but DJ has nothing for this category | 1% |
Input contain multiple words present across multiple DJ categories | 1% |
If one the following information changed, the alert for instance set as “false positive” will be changed back as “new” and will need to be reviewed.
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You can set custom parameters if you use the post_filtering_alias
parameter when doing your transactional name screening. These parameters allow to filter out more results using more precise parameters and are applied on top of the name-search internal filtering.