Activity Graph Database for Cross-Correlated Data Management

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Solution Overview

Problem

Relational database systems face inefficiencies in managing complex relationships among users, contents, and actions due to the need for join operations and normalization, which incur overhead and limit flexibility in storing and querying associated data.

Innovation Solution

An activity graph database is employed, using nodes and edges to represent users, contents, actions, and their relationships, allowing for efficient storage, association, and retrieval of correlated data while capturing changes over time without losing historical states.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If relational database systems are used to manage complex relationships among users, contents, and actions, then data can be stored using related tables with primary keys and foreign keys, but join operations and normalization incur overhead and limit flexibility in storing and querying associated data

Engineering Contradiction:

Improveflexibility in storing and querying associated dataVSAvoidoverhead from join operations and normalization

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the data model into distinct node types (user nodes, content nodes, action nodes) and relationship types, allowing each to be managed independently while maintaining clear associations. This segmentation eliminates the need for complex join operations by directly representing relationships as first-class citizens in the graph structure.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent transitions from the traditional two-dimensional relational table structure to a multi-dimensional graph structure where nodes and edges represent entities and relationships respectively. This dimensional change enables direct representation of complex relationships without requiring multiple normalization steps or join operations across multiple tables.

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

2Productivity

If traditional relational databases are used, then data can be organized in tables, but the need for join operations increases processing overhead and reduces query efficiency for complex relationships

Engineering Contradiction:

Improvequery efficiency for complex relationshipsVSAvoidprocessing overhead from join operations

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent performs preliminary action by pre-establishing and storing relationships as direct edge connections between nodes in the graph database. This eliminates the need for runtime join operations, as the relationships are already resolved and stored in their final form, allowing for immediate retrieval without additional processing overhead.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent creates a direct copy of the relationship structure in the graph database, where edges represent relationships just as tables represent data. This copying of the relational structure into a native graph format eliminates the need for join operations by allowing direct traversal of relationships through the graph edges.

Inventive Principle:

Principle #26Copying

3Reliability

If relational databases use primary keys and foreign keys to capture associations, then data integrity can be maintained, but the complexity of managing cross-references between tables increases

Engineering Contradiction:

Improvedata integrity through associationsVSAvoidcomplexity of managing cross-references

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent merges the entity representation and relationship representation into a unified graph structure where nodes represent entities and edges represent relationships. This merging eliminates the need for separate primary key and foreign key mechanisms, as the graph structure inherently maintains relationships through its connected topology, reducing the complexity of managing cross-references.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces edge nodes as intermediaries that represent relationships between user nodes and content nodes. These edge nodes serve as mediators that maintain the associations between entities without requiring direct foreign key references, simplifying the management of cross-references by centralizing relationship information in the edge structure.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS8825711B2Managing cross-correlated data

Publication Date: 2014.09.02 MAGNET SYSTEMS INC

AI summary

Systems and processes for storing correlated data in a graph database are described. A first user node may be stored. In response to a request, a first event node and a second user node may be stored. The first event node may be associated with the first user node through an edge indicating participation. The first event node may be associated with the second user node through an edge indicating participation. In response to a content access, a second event node and a content node may be stored. The second event node may be associated with the first user node through an edge indicating participation. The second event node may be associated with the content node through an edge indicating usage. The first user node may be associated with the content node through an edge indicating the first user node handles the content node.