Enterprise Content Indexing for Stress-Point Information Retrieval
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Solution Overview
Problem
Existing enterprise systems lack the ability to efficiently identify and retrieve relevant information related to enterprise problems, opportunities, and unexpected events, making it difficult for users to address these issues effectively.
Innovation Solution
A system and method that indexes current and past enterprise content to enrich knowledge about problems, opportunities, or events, using a computing device to scan, parse, and index content, and provide relevant information to users, with a focus on enterprise stress points and goal proximity to determine relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system scans and indexes all enterprise content to enrich knowledge, then the completeness of information increases, but the system complexity and processing time increase
Solution Approach 1:
The patent segments enterprise content into distinct types (emails, documents, application data, web content) and processes each type through specialized scanning and indexing mechanisms. This segmentation allows the system to manage complexity by handling different content types independently while maintaining comprehensive coverage of all enterprise information.
Solution Approach 2:
The patent introduces an intermediary indexing layer that sits between the raw enterprise content and the user queries. This index structure acts as a mediator, pre-processing and organizing content in advance so that when queries are made, the system can quickly retrieve relevant information without scanning entire content repositories, thus reducing processing complexity.
2Loss of information
If the system provides all scanned content to users, then the information availability increases, but the information relevance and noise level worsen
Solution Approach 1:
The patent applies local quality by providing different levels and types of information relevance to different users based on their specific needs, roles, and the nature of the problem they are addressing. Rather than providing uniform information to all users, the system tailors the relevance assessment to local user contexts, ensuring each user receives appropriately filtered information.
Solution Approach 2:
The system incorporates feedback mechanisms where user interactions with retrieved information are analyzed to improve future relevance assessments. The system learns from user behavior patterns and adjusts its relevance determination algorithms, creating a continuous improvement loop that enhances information precision over time while maintaining broad availability.
3Speed
If the system notifies users of all problems and events, then the responsiveness increases, but the notification overload and user attention worsen
Solution Approach 1:
The patent applies partial action by notifying users selectively rather than universally. The system determines which users should receive notifications based on their roles, the nature of the problem or event, and their relationship to the affected processes. This partial notification approach maintains rapid response capability for critical issues while avoiding overwhelming users with irrelevant alerts.
4Adaptability or versatility
If the system scans diverse content types (emails, documents, application data, web content), then the coverage increases, but the processing complexity and resource requirements increase
Solution Approach 1:
The patent implements a universal scanning and indexing framework that can handle multiple content types (emails, documents, application data, web content) through a common architecture. This multi-functional approach allows the system to process diverse content types using the same core mechanisms, reducing the need for separate specialized processors for each content type and thereby optimizing resource utilization.
Data Source
AI summary
A system and method are provided for finding and retrieving information within an enterprise that is relevant to enterprise problems, enterprise opportunities, and unexpected or interesting events. The method includes scanning content related to a process conducted by an enterprise, where the process includes one or more process steps; identifying a problem, opportunity or event associated with a process step (an enterprise stress point); indexing the scanned content with respect to the enterprise stress point; determining whether the scanned content is information relevant to the problem, opportunity or event; and providing relevant information to a user. The relevant information includes a description or discussion of a contemporaneous or previous experience of the enterprise regarding the problem, opportunity or event.


