Privacy Recommendation Engine for Online Vendor Matching
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Solution Overview
Problem
Data subject users face difficulties in understanding and enforcing their data privacy protection rights due to lengthy and complex privacy policies and terms of service from data processors and controllers, which are often not readily visible or updated, leading to unclear disclosure of data collection and processing methods.
Innovation Solution
A computer-implemented method and system that creates an entity user account with a graphical user interface to display privacy rights education prompts and scores, assigning a unique alpha-numeric identifier for matching users with online vendors, providing optimized privacy rights recommendations, and offering financial rewards for scoring and referring services, while continuously updating privacy education based on user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data processors and controllers provide detailed privacy policies and terms of service, then data subject users can understand their privacy rights, but the policies become lengthy and complex making them difficult to understand
Solution Approach 1:
The patent segments complex privacy policies into discrete, scorable elements that can be individually evaluated. The system breaks down lengthy legal documents into specific privacy practice components that users can assess separately, transforming an overwhelming monolithic document into manageable segments.
Solution Approach 2:
The patent introduces an intermediary scoring system and recommendation engine that mediates between the complex privacy policies and users. This intermediary layer translates legal jargon into simplified scores and actionable recommendations, making privacy information accessible without requiring users to directly interpret complex legal text.
2Loss of information
If privacy policies are made readily visible and updated, then users can access current information, but the volume of information increases making it harder to locate key terms
Solution Approach 1:
The patent replaces the mechanical process of manually searching through text with an automated information retrieval system. The system uses electronic databases, search algorithms, and recommendation engines to automatically locate and present relevant privacy information based on user needs, eliminating the need for users to manually scan through documents.
Solution Approach 2:
The patent changes the parameter of information presentation from raw text to structured, scored data. By transforming privacy policy information into quantifiable scores and categorized attributes, the system enables efficient filtering, sorting, and retrieval of relevant information based on user-specific criteria.
3Reliability
If users manually review privacy policies to understand data collection methods, then they can make informed decisions, but the process requires significant time and effort
Solution Approach 1:
The patent performs preliminary analysis of privacy policies before users need to make decisions. The system pre-processes, scores, and categorizes privacy information in advance, so when users need to make informed decisions, the analysis is already complete and presented in an easily consumable format.
Solution Approach 2:
The patent enables privacy information to serve itself by automatically generating scores, recommendations, and alerts without requiring user intervention. The system autonomously monitors privacy policies, detects changes, and presents relevant information to users based on their profiles and preferences.
Data Source
AI summary
A system and method for dynamically optimizing online privacy recommendations for entity users. Certain aspects of the present disclosure provide for methods and systems for optimizing an entity privacy rights recommendation in online transactions. In certain embodiments, an entity user creates an account within an end user application comprising a graphical user interface configured to display one or more privacy rights education prompt and an entity user privacy score. The entity user is assigned a unique alpha-numeric identifier for the entity user within the entity user account. The end user application is configured to match the entity user to one or more online category good or service vendor according to the unique alpha-numeric identifier and provide an entity privacy rights recommendation comprising the one or more online category good or service vendor matched to the entity user.