How does secondary attributes-matching work?

Matching named entities requires algorithms to determine how data should be matched. In this regard, we distinguish name-matching algorithms from secondary attributes-matching algorithms.

Matching names requires a threshold value between 0 and 100%. This value helps to determine the point where it becomes highly probable that two names are the same.

In addition to name matching, it is also possible to apply specific matching algorithms to secondary attributes (e.g., date of birth, address, nationality). Using secondary attributes-matching algorithms helps to automatically discard irrelevant matches (i.e., false positives) by leveraging more data points than names alone.

You can check Screena Plus endpoints to find out all secondary attributes available per type of entity (i.e., individuals, organizations, vessels).

Here is a code example of how to search an individual with date of birth as a secondary attribute.

This request uses the date-matching algorithm dateOfBirthAlgo to match dates of birth within the same year:

{
	"queries": [{
		"sourceData": [{
			"names": [{
				"fullName": "Adan Antonio Blanco Rodriguez"
			}],
			"datesOfBirth": [{
				"date": "1968-03-18"
			}]
		}],
		"targetData": [{
			"datasets": [{
				"label": "USA"
			}]
		}],
		"threshold": 0.8,
		"dateOfBirthAlgo": {
			"type": "same_year"
		}
	}]
}