Centralized Identity for Cross-Platform Data Personalization
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Solution Overview
Problem
Existing systems face challenges in parsing and aggregating vast amounts of user data across disparate platforms to provide personalized experiences, as these datasets are maintained by different entities without data pipelining technology, making it difficult to quickly and accurately determine user-specific data for real-time application modifications.
Innovation Solution
The generation of a centralized identity that associates user identifiers across multiple resources, allowing for the aggregation and personalization of user-related data through a payment service that queries and aggregates data from various resources, using machine learning models to determine similarities and apply dynamic personalizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is aggregated from multiple disparate resources without centralized identity, then data coverage is improved, but data parsing accuracy deteriorates
Solution Approach 1:
The patent introduces a centralized identity as an intermediary that mediates between multiple disparate resources and the data aggregation process. This centralized identity serves as a unique key to accurately match and associate user data across different platforms and resources, resolving the contradiction by enabling both broad data coverage and precise data parsing through the use of a central reference point
Solution Approach 2:
The centralized identity functions universally across multiple disparate resources, serving as a common identifier that works across different platforms, applications, and data sources. This multi-functional identifier enables accurate data aggregation from diverse sources without compromising parsing accuracy, as the same centralized identity can be used to match user data across any number of resources
2Device complexity
If data aggregation is performed without centralized identity, then system complexity is reduced, but personalization accuracy deteriorates
Solution Approach 1:
The patent merges the identification function across multiple resources into a single centralized identity system. Instead of maintaining separate identification systems for each resource, the centralized identity consolidates these functions, enabling accurate personalization by reliably associating user data across resources while managing system complexity through consolidation rather than proliferation of separate systems
3Speed
If real-time data aggregation is attempted without centralized identity, then response speed is improved, but data matching accuracy deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-establishing the centralized identity framework before data aggregation operations. The centralized identity structures are prepared in advance, creating a ready-made matching system that enables rapid real-time data aggregation without compromising accuracy. The pre-configured identity framework allows for fast data matching operations while maintaining high precision through the organized structure
Data Source
AI summary
Techniques described herein are directed to centralized identities for personalization of data presentation. A centralized identity is generated when similar user identifiers as stored across resources are determined. The centralized identity associates the user identifiers with each other and allows for user-related data from the multiple disparate resources to be queried and received. This user-related data can then be utilized to determine one or more personalizations to apply, and an application being used by the user may be modified to present the personalizations.