Temporal Graph Generation with Time-Bound Community Lifecycles

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Solution Overview

Problem

Existing graph generation methods fail to account for the temporal evolution and extinction of communities, are inefficient in generating graphs with time-bound communities, and lack flexibility in accommodating user-specified distributions, especially in large-scale scenarios.

Innovation Solution

A method and device for generating a temporal graph with time-bound communities through node grouping, time window binding, and temporal edge linking, utilizing power-law and uniform distributions for node and time window characteristics, and an index structure transferable between communities to efficiently generate temporal edges.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If existing graph generation methods are used, then graph data can be generated, but they fail to account for temporal evolution and extinction of communities

Engineering Contradiction:

Improveaccuracy of temporal representationVSAvoidcapability to model community extinction

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent introduces dynamic time windows that can start and end at different times, allowing communities to be active during specific periods and then disappear. This dynamic approach enables the model to capture temporal evolution and extinction of communities, transforming static graph generation into a dynamic process that reflects real-world community behavior over time.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent changes the parameter model from static to dynamic by introducing time window parameters (start time, end time, duration) that can vary for different communities. This allows the generation model to accommodate different temporal patterns, including community formation and extinction, thereby improving reliability of temporal representation while maintaining adaptability.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If existing temporal graph generation algorithms are used, then temporal dynamics can be captured, but they focus solely on community formation and ignore extinction processes

Engineering Contradiction:

Improveaccuracy of temporal dynamics representationVSAvoidcompleteness of community lifecycle modeling

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent segments the community lifecycle into distinct phases: formation phase (community creation), active phase (community operation with time windows), and extinction phase (community dissolution). This segmentation allows the model to independently model each phase, ensuring complete coverage of community lifecycle while maintaining computational efficiency and avoiding redundant processing.

Inventive Principle:

Principle #1Segmentation

3Adaptability or versatility

If graph generation methods are used without distribution constraints, then generation is simple, but they cannot meet user-specified distribution requirements

Engineering Contradiction:

Improveflexibility in accommodating user requirementsVSAvoidcomplexity of distribution control mechanism

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements parameter change by allowing users to specify distribution parameters (power-law exponent for community size, uniform distribution for time windows) and adjusting the generation process accordingly. The model can switch between different distribution modes and parameter settings, providing flexibility to meet diverse user requirements while maintaining a unified generation framework that avoids excessive complexity.

Inventive Principle:

Principle #35Parameter changes

4Productivity

If existing graph generation methods are used, then generation process is simple, but efficiency is insufficient in large-scale scenarios

Engineering Contradiction:

Improvegeneration efficiencyVSAvoidcomplexity of generation process

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent applies preliminary action by pre-defining the temporal structure and community characteristics before generating the actual graph. Time windows and community parameters are established in advance, allowing the generation process to proceed more efficiently by filling in details rather than constructing everything from scratch. This reduces computational complexity while maintaining high generation efficiency for large-scale scenarios.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250335507A1Method and device for generating temporal graph with time-bound communities

Publication Date: 2025.10.30 TSINGHUA UNIVERSITY

AI summary

The present disclosure relates to at least: grouping a set of nodes in a target scenario to obtain nodes included in each of a plurality of time-bound communities; the numbers of nodes in the communities follow a power-law distribution; generating a time window for each of the plurality of time-bound communities, wherein starting times of time windows corresponding to the plurality of time-bound communities follow a uniform distribution, and lengths of the time windows corresponding to the plurality of time-bound communities follow a power-law distribution; and constructing an index structure that is transferable between different time-bound communities, and generating temporal edges within each time-bound community and/or temporal edges between different time-bound communities of the plurality of time-bound communities based on the nodes included in the respective time-bound communities, the time windows of the respective time-bound communities, and the index structure, thus generating a temporal graph for a target scenario.