Knowledge Space Analytics for Unified Knowledge Representation
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Solution Overview
Problem
Current technologies lack integrative, operational, and visually engaging solutions for representing and analyzing knowledge spaces, unlike geographic spaces, which hampers effective communication and collaboration among knowledge workers with diverse disciplinary backgrounds.
Innovation Solution
A system and method that involves training multiple topic models, filtering and harmonizing them, and using these models to create a base map model, which is visualized and served through a map server, allowing for text-based, document-based, and map-based queries to integrate knowledge artifacts into a unified knowledge space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If geographic mapping technologies are used for knowledge spaces, then visual and analytical capabilities are improved, but device complexity increases because no such technologies currently exist for knowledge spaces
Solution Approach 1:
The patent introduces topic models as intermediary structures that bridge text documents and visual knowledge space representations. These topic models serve as mediators that transform unstructured text into structured spatial representations, enabling geographic mapping technologies to be applied to knowledge spaces without directly complexifying the core system.
Solution Approach 2:
The base map model serves multiple functions: it provides visual representation of knowledge spaces, enables spatial querying, supports analytical operations, and facilitates communication among knowledge workers. This multi-functionality reduces the need for separate specialized systems, thereby managing complexity while delivering comprehensive capabilities.
2Adaptability or versatility
If multiple topic models are trained and harmonized to represent diverse knowledge domains, then adaptability and integration capability are improved, but device complexity increases due to the need for filtering and harmonization processes
Solution Approach 1:
The patent segments the knowledge representation task into multiple independent topic models, each handling specific aspects or domains of knowledge. These segmented models are then filtered and harmonized to work together, allowing the system to manage diversity and complexity through modular organization rather than attempting to create a single monolithic model.
Solution Approach 2:
The filtering and harmonization of topic models is performed in advance during system setup, creating a pre-processed unified knowledge base. This preliminary action eliminates the need for complex real-time processing during knowledge worker interactions, thereby reducing operational complexity while maintaining high adaptability.
3Loss of information
If a unified knowledge space platform is created to integrate knowledge artifacts, then communication effectiveness is improved, but device complexity increases due to the need for base map models and query systems
Solution Approach 1:
The patent creates simplified copy representations of complex knowledge artifacts through the base map model. Instead of managing the full complexity of original knowledge artifacts, the system works with condensed spatial representations that preserve essential relationships and meanings, thereby reducing platform complexity while maintaining communication effectiveness.
Data Source
AI summary
Provided herein is topic modeling involving multiple topic models being combined to create high-dimensional knowledge reference systems, the creation of detailed, multi-scale base maps from large numbers of documents, and analytical operators that integrate reference systems and base maps to enable search, visualization, and analytics on text documents.