Context-Based Graph Node Search via Synthetic Event Nodes
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Solution Overview
Problem
Current database systems, particularly graph databases, face challenges in effectively searching for and associating data stores with entities represented by nodes, as they lack a context-based approach to link nodes, edges, and data structures efficiently.
Innovation Solution
A context-based system is introduced that utilizes a graph database with synthetic context event nodes to link graph nodes to relevant data stores through pointers, enabling efficient retrieval of data stores related to entities by describing attributes and relationships within the graph database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a graph database stores data statically without context-based linking, then data storage is simple, but the ability to search for and associate data stores with entities is ineffective
Solution Approach 1:
The patent introduces a context database as an intermediary layer between the graph database and data stores. The context database contains context records that link graph nodes to data stores through contextual relationships, enabling effective data association without directly modifying the graph database structure. This mediator approach resolves the contradiction by providing enhanced search capability while maintaining relative structural simplicity.
Solution Approach 2:
The system segments the data architecture into distinct components: the graph database for entity relationships, the context database for contextual associations, and data stores for detailed information. This segmentation allows each component to serve its specific function efficiently, improving search capability while keeping the overall system complexity manageable through clear separation of concerns.
2Loss of information
If pointers directly link graph nodes to data stores, then association is efficient, but the system lacks contextual information about relationships
Solution Approach 1:
The context database serves as a mediator that stores contextual information about relationships between graph nodes and data stores. Instead of direct pointers that lose contextual nuance, the context database captures detailed relationship descriptors, allowing the system to retrieve both the association and the contextual meaning without excessive structural complexity.
Solution Approach 2:
The patent adds a new dimensional layer (the context database) to the traditional graph-node-to-data-store linkage. This additional dimension stores contextual information that would be lost in direct pointer relationships, enriching the data model without requiring complex modifications to existing graph database structures.
3Productivity
If a synthetic context event database is introduced to link nodes and data stores, then data retrieval becomes context-aware, but the system complexity increases
Solution Approach 1:
The context database is pre-populated with context records that establish relationships between graph nodes and data stores before retrieval operations occur. This preliminary action enables fast, context-aware data retrieval without requiring complex real-time computations, thus improving productivity while keeping the structural complexity manageable through advance preparation.
Solution Approach 2:
The system creates a contextual copy or representation of relationships in the context database, separate from the original graph database. This copying approach allows efficient context-aware retrieval by working with the pre-established context records, rather than querying the complex graph structure during retrieval operations.
Data Source
AI summary
A graph database storage system contains a graph database that has multiple graph nodes. A first pointer points from a particular graph node to a particular synthetic context event node in a synthetic context event database. A second pointer points from the particular synthetic context event node in the synthetic context event database to a particular data store in a data structure, such that the first pointer and the second pointer associate the particular data store with the particular entity represented in the graph database via the particular synthetic context event node.