providing intelligent experiences, such as identity resolution with fuzzy first name matching and soft-matching. This solution addresses the challenge of duplication of records while providing the ability to tailor matching for different industries. And now, we’ve added control in fuzzy matching to include not only first name, but all features! By introducing fuzzy matching to all features we are empowering our customer by allowing for more flexible and inclusive matching criteria, accommodating variations in personal data entry and enabling accurate recognition even with minor discrepancies, thus ensuring a smoother and more personalized user experience.
Lets dive into the AI that is powering this new capability!
Two-Step Framework for Identity Resolution
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Lets begin by reviewing our general, two-step framework for identity afghanistan phone number list resolution. To perform identity resolution, the first step after ingesting data is to cluster similar profiles together. This is referred to as the candidate selection step. This step is crucial for efficiency – with clusters of similar profiles, the search for matching identities is reduced to profiles within the same cluster, instead of the millions of profiles across all data sources. After clusters of similar profiles are formed, the matching step is next. In the matching step, a target profile and its candidates (profiles within the same cluster) are more carefully compared to determine the final matching and resolution of identities.