Dynamic Procurement Data Mining for Privacy-Preserving Decision Inference
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Solution Overview
Problem
Existing resource allocation techniques lack the ability to reliably infer decisions of one organization, leading to less optimal decisions by other organizations, resulting in inefficiencies that ripple across the interconnected landscape of organizations.
Innovation Solution
A computer system that ingests context information, public data, and record data, normalizes them, determines weights for each, and generates predicted resource allocation information, which is then displayed, allowing organizations to make more informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations analyze data locally to protect competitive advantage and privacy, then data security and privacy are improved, but the ability to infer decisions of other organizations and make optimal resource allocation decisions deteriorates
Solution Approach 1:
The patent introduces a data analytics platform as an intermediary that processes public data and infers organizational decisions without requiring direct access to private internal data. The system acts as a mediator between organizations, enabling decision inference through public information sources while maintaining data security and privacy boundaries.
Solution Approach 2:
The patent replaces traditional direct data access mechanisms with an information inference mechanism. Instead of directly accessing internal organizational data, the system uses public data sources and analytical algorithms to substitute and infer decision-making patterns, achieving the same analytical goal without compromising data security.
2Reliability
If providing organizations do not have reliable knowledge of each other's decisions, then data privacy is maintained, but resource allocation efficiency deteriorates
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring public data sources, inferring organizational decisions, and providing predictive insights back to providing organizations. This feedback loop enables organizations to adjust their resource allocation strategies based on inferred decisions of competitors and partners, improving overall efficiency.
Solution Approach 2:
The patent applies preliminary action by proactively inferring and predicting organizational decisions before they are publicly announced or finalized. The system analyzes public data in advance to forecast resource allocation patterns, allowing organizations to prepare and optimize their own strategies ahead of time.
Data Source
AI summary
Systems, methods, and computer-readable medium storing instructions for generating predicted resource allocation information of an organization based on dynamically ingested data, including ingesting context information, ingesting public data, ingesting record data, normalizing the public data with the record data, determining a first set of weights corresponding to the record data and a second set of weights corresponding to the public data, generating predicted resource allocation information, and causing the predicted resource allocation information to be displayed. In some aspects, additional information may be received or ingested, including one or more of additional public data, additional private data, or feedback from a user. The additional information may be used for adjusting one or more of the first set of weights or the second set of weights.