Atomic Knowledge Representation for Relevance and Complexity
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Solution Overview
Problem
The sheer volume of digital content poses challenges in determining what information is of interest to users, leading to issues in presenting relevant information without overwhelming them with irrelevant data.
Innovation Solution
A system that utilizes an atomic knowledge representation model, combining elemental data structures with generative rules to create and manage knowledge representations, allowing for the identification and presentation of relevant content to users by synthesizing new knowledge as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a system stores and processes large volumes of digital content to provide comprehensive information, then information completeness is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent segments the knowledge representation system into atomic knowledge units that can be independently stored, retrieved, and processed. Each atomic unit represents a discrete fact or concept, allowing the system to manage large volumes of information through modular organization rather than monolithic storage, thereby reducing system complexity while maintaining information completeness.
Solution Approach 2:
The patent introduces an intermediary layer (the atomic knowledge representation system) between the raw digital content and the user query processing. This intermediary transforms unstructured content into standardized atomic knowledge units with defined schemas, enabling efficient retrieval and reducing the complexity of direct content processing.
2Loss of information
If a system processes and presents comprehensive digital content to users, then information relevance is improved, but data volume and processing overhead increase
Solution Approach 1:
The patent extracts only the essential and relevant atomic knowledge units needed to answer user queries from the larger corpus of digital content. By selecting and presenting only the necessary atomic units rather than processing entire documents or content blocks, the system maintains information relevance while significantly reducing the effective data volume handled during query processing.
Solution Approach 2:
The patent applies local quality by tailoring the presentation of atomic knowledge units to specific user needs and query contexts. Different users receiving different subsets of relevant atomic units based on their specific information needs, rather than presenting uniform comprehensive content to all users, reduces overall data volume while maintaining relevance.
3Ease of operation
If a system customizes knowledge representation for individual users, then user experience is improved, but system complexity and maintenance costs increase
Solution Approach 1:
The patent creates a universal atomic knowledge representation schema that serves multiple users and purposes. The same standardized atomic units can be reused across different user contexts and query types, enabling customization of user experience through selective assembly of universal building blocks rather than creating separate customized systems for each user, thereby reducing maintenance complexity.
Solution Approach 2:
The system enables self-service customization where users can interact with the standardized atomic knowledge units in ways that naturally suit their needs, and the system automatically assembles relevant atomic units based on query analysis. This automated assembly process reduces the need for manual system configuration and maintenance while still providing personalized user experiences.
Data Source
AI summary
Techniques for customizing knowledge representation systems including identifying, based on a plurality of concepts in a knowledge representation (KR), a group of one or more concepts relevant to user context information, and providing the identified group of one more concepts to a user. The KR may include a combination of modules. The modules may include a kernel and a customized module customized for the user. The kernel may accessible via a second KR.