Work Assistant Search Optimization with Privacy-Safe Diagnostic Logs
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Solution Overview
Problem
Existing enterprise knowledge management platforms face challenges in optimizing work assistant search engines due to limited access by third-party providers to confidential company data, necessitating a system to monitor and improve search quality without compromising data security.
Innovation Solution
A system and method that utilizes non-personally-identifiable information to monitor and optimize work assistant search engines by recording diagnostic data in a highly-granular fashion, excluding personal and confidential information, and transmitting this data to a separate computing environment for analysis and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If third-party providers are given access to confidential company data for optimization purposes, then search engine optimization improves, but data security deteriorates
Solution Approach 1:
The patent extracts only the necessary diagnostic information (search queries, result rankings, user interactions) from the enterprise environment while leaving confidential data behind. This extraction is performed through automated agents that collect minimal required data for optimization purposes without exposing sensitive company information to third-party providers.
Solution Approach 2:
The patent introduces an intermediary layer (automated diagnostic agents and data processing systems) that mediates between the enterprise environment and third-party providers. This intermediary processes and anonymizes data locally before transmission, enabling optimization collaboration while maintaining data security boundaries.
2Measurement precision
If detailed diagnostic data is collected for monitoring, then search quality measurement improves, but information privacy deteriorates
Solution Approach 1:
The patent applies different data collection strategies to different elements: detailed metrics are collected for search quality measurement (queries, rankings, interactions) while personally identifiable information is excluded or anonymized. This local differentiation allows precise measurement without compromising user privacy.
Solution Approach 2:
The patent transforms raw diagnostic data into aggregated metrics and anonymized statistics that preserve search quality information while removing identifying characteristics. Data parameters are changed from individual user-level details to population-level patterns suitable for optimization analysis.
Data Source
AI summary
A system and method for monitoring and optimizing work assistant search engines implemented within secured enterprise computing systems include one or more processing devices to receive diagnostic data of a work assistant search engine from a secured enterprise computing system. The one or more processing devices may further determine, by analyzing the diagnostic data, a search quality metric value associated with the feature values and the scores. Responsive to determining that the search quality metric value differs from a target search quality metric value by a predetermined threshold value, the one or more processing devices may further determine an updated score model, and provide the updated score model to the secured enterprise computing system to update the work assistant search engine.