Automated Knowledge Capture via Email Content Matching
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Solution Overview
Problem
Existing knowledge management systems face challenges in identifying and capturing knowledge resources within organizations, as manual input of information is time-consuming and often incomplete, leading to low user compliance and participation, and the cost of centralized staff required for sophisticated systems can be a deterrent.
Innovation Solution
A method and system that automatically captures knowledge by analyzing electronic documents, such as e-mail messages, to construct user knowledge profiles, which are then used to suggest appropriate recipients for communications based on content matching, reducing the need for manual input and centralized staff.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual input of knowledge information is required, then knowledge can be captured in pre-defined fields, but user compliance and participation fall to inadequate levels due to time-consuming effort
Solution Approach 1:
The system enables automatic population of knowledge fields by extracting information from electronic documents and matching them with user profiles. The sender computer automatically performs the knowledge capture function that would otherwise require manual user input, thereby resolving the contradiction between information completeness and time investment.
Solution Approach 2:
The patent replaces the mechanical manual input process with an automated electronic system. The system uses computer-based document analysis and profile matching algorithms to substitute human manual effort in populating knowledge fields, thereby reducing time loss while maintaining or improving information completeness.
2Reliability
If sophisticated knowledge management systems are implemented with centralized staff, then knowledge capture can be improved, but costs increase significantly deterring initial funding
Solution Approach 1:
The system performs knowledge capture automatically without requiring centralized staff intervention. The automated document analysis and profile matching functions replace the need for dedicated knowledge management personnel, thereby maintaining reliable knowledge capture while eliminating the costly human resource requirement.
Solution Approach 2:
The patent substitutes the mechanical system of centralized staff with an automated electronic knowledge management system. The computer-based system performs all knowledge capture, organization, and distribution functions that would otherwise require human staff, thereby reducing costs while maintaining or improving thoroughness.
3Quantity of substance
If manual knowledge input is required, then knowledge repositories can be built, but user participation remains low as users experience inconvenience before experiencing benefits
Solution Approach 1:
The system automatically builds the knowledge inventory by extracting information from electronic documents without requiring user action. Users simply send or receive documents as part of normal communication, and the system autonomously captures and organizes the knowledge, thereby increasing participation while maintaining ease of operation.
Solution Approach 2:
The system performs preliminary knowledge capture by automatically analyzing documents before they need to be manually entered into the repository. By pre-extracting and organizing knowledge information from incoming documents, the system builds the knowledge inventory in advance without requiring user effort, thereby increasing both inventory quality and user convenience.
4Productivity
If automated knowledge capture is implemented through content analysis, then user compliance increases, but system complexity increases requiring sophisticated algorithms
Solution Approach 1:
The system extracts only the essential knowledge elements from electronic documents that are relevant to user profiles. By selectively extracting specific information rather than processing entire documents, the system achieves high knowledge capture productivity while limiting the complexity of the analysis algorithms to only what is necessary for the extraction task.
Data Source
AI summary
A method of addressing a communication, such as an e-mail, for transmission over a network is disclosed. A knowledge server accesses a descriptive profile for each of a number of potential recipients of the communication. A subset of the potential recipients is identified as suggested recipients based on detected correspondences between the content of the communication and the contents of the respective descriptive profiles for the potential recipients. The subset of suggested recipients is then presented to the sender of the communication, in conjunction with an indication of the correspondence between the content of the communication and the contents of the respective descriptive profiles. The indication of the correspondence may, for example, include highlighting terms within the communication that match published terms within the descriptive profiles of the suggested recipients.