Identity Graph Edge Pruning for Collapsed Profile Resolution
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Solution Overview
Problem
Existing identity resolution systems face inefficiencies in handling collapsed identity graphs, leading to undesired customer experiences due to mistaken identities, misleading analytics, and ineffective personalization efforts, while manual data management increases computing and network resource usage.
Innovation Solution
Automatically evaluate properties such as time and priority of edges in collapsed identity graphs to resolve them efficiently, pruning edges that cause graph collapse and updating customer profiles with the most up-to-date data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data management is used to handle collapsed identity graphs, then accuracy can be maintained, but computing and network resource usage increases
Solution Approach 1:
The system automatically evaluates and prunes edges from collapsed identity graphs without requiring manual intervention. The identity resolution component autonomously determines which edges to remove based on predefined criteria, enabling the system to self-maintain accurate customer profiles while reducing resource consumption compared to manual management processes
2Use of energy by moving object
If automatic edge evaluation is implemented, then computing resource usage is reduced, but system complexity increases
Solution Approach 1:
The system evaluates edges based on changing parameters such as time and priority values. By dynamically assessing edge properties and pruning those that no longer meet criteria, the system achieves automatic management with reduced computing resources. The predefined evaluation criteria simplify the complexity by providing clear decision rules for edge removal
3Stability of the object's composition
If collapsed identity graphs are not resolved, then data consistency is maintained, but customer profile accuracy deteriorates
Solution Approach 1:
The system performs preliminary evaluation of edges before finalizing customer profiles. By pre-assessing which edges should be pruned based on time and priority criteria, the system maintains data consistency while ensuring customer profile accuracy. This preliminary action prevents inaccurate data from being incorporated into profiles
Data Source
AI summary
Methods and systems are provided for evaluating edges of collapsed identity graphs for identity resolution. In embodiments described herein, a collapsed state of identity graphs, such as based on an identity namespace limit being exceeded by the identity graphs, is determined by applying an identity node and edge of an incoming record to the identity graphs. A temporary state of the identity graphs is determined by pruning edges of the collapsed state. A non-collapsed state of the identity graphs that includes the edge of the incoming record is determined by applying the edge of the incoming record to the temporary state. A different edge is determined to be pruned from the non-collapsed state as when the different edge is applied to the temporary state with the edge of the incoming record, the temporary state collapses into the collapsed state. An identity graph is updated based on the non-collapsed state.