Multi-layered Action Graph Database for Knowledge Representation
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Solution Overview
Problem
Existing knowledge representation systems using graph databases face challenges with high I/O latency, scalability issues, and inefficiencies in capturing action capabilities of real-world entities, particularly in managing large volumes of sparse and dynamic data.
Innovation Solution
A multi-layered database system comprising an action graph layer, a standard graph layer, and a backend database layer, where action graph layer captures action capabilities of real-world entities as distinct nodes, enabling flexible and extensible knowledge representation, and the standard graph layer with pluggable indexing architecture facilitates efficient data retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If graph databases are used to store large volumes of dynamic and sparse datasets, then storage capacity and query retrieval capability are improved, but I/O latency increases and scalability becomes problematic
Solution Approach 1:
The patent segments the graph database into multiple layers: a first layer for storing action capability information with frequent access patterns, and a second layer for storing additional information with less frequent access. This segmentation allows the system to optimize I/O operations by accessing only the necessary layers, reducing overall I/O latency while maintaining large storage capacity.
Solution Approach 2:
The patent introduces a hierarchical dimension to the traditional flat graph database structure. By organizing data across multiple layers with different access frequencies and characteristics, the system transforms a two-dimensional storage approach into a multi-dimensional architecture that optimizes both storage capacity and retrieval performance.
2Productivity
If graph structures are used to represent and store datasets with diverse relations, then information retrieval capability is improved, but device complexity increases
Solution Approach 1:
The patent divides the graph database into distinct layers, each handling specific types of data and relationships. The first layer manages action capability information while the second layer handles additional information, simplifying the overall system architecture by dividing complex storage and retrieval operations into manageable segments.
Solution Approach 2:
The patent introduces an intermediary indexing structure that maps between the multiple layers of the graph database. This intermediary layer simplifies queries by providing a unified interface for accessing data across layers, reducing the complexity of navigating the hierarchical structure while maintaining efficient information retrieval.
3Adaptability or versatility
If action capabilities of real-world entities are captured as distinct nodes, then knowledge representation flexibility is improved, but data structure complexity increases
Solution Approach 1:
The patent segments the knowledge representation into distinct components: action capability nodes, participant entity nodes, and relationship edges. This segmentation allows the system to maintain high flexibility in representing diverse action capabilities while managing complexity through structured organization of these segments.
Solution Approach 2:
The patent creates a universal node structure for action capabilities that can represent various types of actions across different domains. By using a standardized multi-functional node design, the system achieves high adaptability for knowledge representation without proportionally increasing structural complexity.
Data Source
AI summary
Knowledge representation in multi-layered database includes systems and methods for storing and retrieving data in the multi-layered database. In the multi-layered database, an action graph database includes participant-entity nodes corresponding to real world entities and action nodes corresponding to action capabilities of the real world entities. Each of the participant-entity nodes and the action nodes is associated with properties, relationships, and relationship properties. Underlying the action graph layer is a standard graph layer that stores nodes, node properties associated with the nodes, edges, and edge properties associated with the edges, wherein the nodes correspond to the participant-entity nodes and the action nodes. Further, underlying the standard graph layer is a backend database layer that stores corresponding data and metadata.