Unified Identity Context for Knowledge Graph Query Accuracy
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Solution Overview
Problem
Maintaining a cloud computing environment with numerous third-party services is complex due to intricate dependencies, security concerns, performance issues, and financial management challenges, which require robust monitoring and alerting systems to address compatibility, vulnerabilities, and performance variability.
Innovation Solution
A system and method that utilizes a knowledge graph to generate unified identities across multiple data sources, applying heuristics to detect and connect identity representations, and process natural language queries to improve the accuracy of language models by generating context-specific responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robust monitoring and alerting systems are implemented to track third-party services, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary system that consolidates identity context from multiple third-party services into a unified knowledge graph. This intermediary layer manages the complexity of monitoring numerous services by creating a centralized representation of identity relationships, allowing reliable tracking without proportionally increasing system complexity
Solution Approach 2:
The patent merges identity information from multiple disparate third-party services into a single unified identity context. By combining scattered identity data points into one consolidated knowledge graph, the system achieves comprehensive monitoring reliability while reducing the overall complexity of managing separate tracking systems for each service
2Measurement precision
If context is generated from multiple identity sources, then query accuracy is improved, but use of energy increases
Solution Approach 1:
The patent performs preliminary action by pre-consolidating identity context from multiple sources into a unified knowledge graph before queries are executed. This advance preparation allows the system to retrieve pre-processed identity information during queries, improving accuracy while reducing the computational energy required at query time compared to generating context from scratch for each query
Data Source
AI summary
A system and method for enhancing query response is presented. The method includes detecting a first identifier of a first identity; detecting a second identifier of a second identity; applying a set of heuristics to the first identifier and to the second identifier to detect a unified identity; generating in a knowledge graph a representation of the first identity, of the second identity, and of the unified identity, wherein the unified identity is connected to the first identity and the second identity; receiving a natural language query; detecting in the received query an identity identifier; traversing the knowledge graph to match the identity identifier to the unified identity; generating a context for a language model based on any one of: the first identity, the second identity, and a combination thereof; generating a prompt based on the context and the query; and processing the prompt to generate a response.