Anonymous Knowledge Sharing via Local Profile Analysis
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Solution Overview
Problem
Current information sharing and knowledge management systems face challenges such as high participation costs, inaccuracy, and loss of privacy, as they require explicit user input and centralized storage of personal data, leading to low participation rates and incomplete knowledge sharing within enterprises.
Innovation Solution
A system and method that generates and maintains user profiles on client computers, allowing anonymous information sharing and scoring through peer-to-peer networks, reducing participation costs by automatically updating profiles and ensuring user privacy through local storage, while using XML protocols for message transmission and statistical analysis for filtering and scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users explicitly describe their personal information and expertise to a centralized database, then the system can provide information recommendations, but participation costs increase and privacy is lost
Solution Approach 1:
The system automatically monitors and tracks user information access patterns, skill set usage, and resource interactions without requiring explicit user input. Users passively contribute data through their natural work activities, eliminating the need to manually describe their expertise while maintaining accurate user profiles for recommendation purposes.
Solution Approach 2:
An intermediary observer component is introduced that sits between users and the information system, automatically capturing and processing user behavior data. This intermediary handles the complexity of data collection and analysis, allowing users to interact naturally with the system without burden while still enabling accurate information matching and recommendations.
2Reliability
If users explicitly update their information on the central database, then the information remains current, but time and effort are required leading to low participation rates
Solution Approach 1:
The observer continuously and automatically monitors user activities, information access patterns, and skill demonstrations in real-time, maintaining up-to-date user profiles without interruption or user intervention. This continuous passive data collection ensures information currency eliminates the need for periodic manual updates.
Solution Approach 2:
The system self-updates user profiles by automatically processing and analyzing user behavior data from various enterprise systems. The profile maintenance function serves itself through automated data capture and processing, completely eliminating the time and effort users would need to invest in manual profile updates.
3Productivity
If users share information openly in the enterprise, then knowledge proliferation increases, but privacy is lost and participation costs increase
Solution Approach 1:
The system processes and analyzes user data locally at individual workstations through observer components, extracting only necessary pattern information for matching purposes. Personal identifiable information remains localized and is not centrally stored or transmitted, maintaining privacy while enabling effective knowledge sharing through pattern-based recommendations.
Solution Approach 2:
Instead of sharing actual personal information or explicit knowledge descriptions, the system creates and shares anonymous behavioral patterns and skill signatures. These copied pattern representations enable effective knowledge matching and recommendation while preserving user privacy, as no actual personal data needs to be exposed or shared across the enterprise.
Data Source
AI summary
One embodiment of the method discloses: identifying an information resource accessed by a client computer; generating an information resource pointer including an address for the information resource; and transmitting a pointer message including the information resource pointer over a network. A second embodiment of the method discloses: generating a client profile; storing the profile; receiving a pointer message containing an information resource pointer; scoring the pointer message with respect to the profile; totaling a number of times that the information resource pointer is received, over a predetermined time period; initializing a timeliness score to a maximum value; decrementing the timeliness score by a predetermined percentage each time a predetermined time period elapses after transmission by a sending client computer; generating an aggregate score; and displaying the pointer message and the aggregate score. The system of the present invention, includes all means for implementing the method.