Graph Edge Simplification via Configurable Strategy Patterns
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Solution Overview
Problem
Current graph processing frameworks are inadequate in handling contextual graph mutations, as they lack support for flexible edge property management and simplification, leading to inconvenient and error-prone processes for data scientists.
Innovation Solution
The implementation of configurable strategies for graph simplification, allowing clients to select and customize strategies to simplify graphs by removing or consolidating edges, with support for imperative and declarative approaches, and optimization techniques to streamline edge property access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If graph mutation operations are supported in current frameworks, then graph analysis flexibility is improved, but the API becomes rigid and error-prone due to undefined semantics for edge properties
Solution Approach 1:
The patent applies parameter changes by transforming the rigid API into a flexible configuration system where edge property semantics are defined through configurable parameters rather than fixed rules. The simplification operation accepts parameters that specify how edge properties should be handled (merge, keep, drop), allowing the same operation to adapt to different semantic requirements without changing the core API structure.
Solution Approach 2:
The patent implements dynamics by making the graph simplification API dynamic and adaptable. Instead of a static, rigid interface with predetermined behavior, the system allows users to dynamically configure edge property handling strategies through parameters and options, enabling the API to adapt to different graph types and analysis contexts while maintaining a consistent interface.
2Productivity
If graph simplification merges all edge properties, then simplification is achieved, but important contextual information is lost
Solution Approach 1:
The patent applies local quality by allowing different edge properties to be handled differently during simplification. Instead of applying a uniform merge operation to all properties, the system enables selective handling where each property can be merged, kept, or dropped based on its specific semantic importance. This localized approach preserves critical information while achieving simplification.
Solution Approach 2:
The patent implements segmentation by dividing edge properties into different categories or groups that can be handled separately. The configuration system allows users to specify different strategies for different property types, effectively segmenting the property handling process. This enables important properties to be preserved while less critical properties are merged or dropped.
3Manufacturing precision
If detailed parameters are specified for each edge property, then precise control is achieved, but API invocation becomes unwieldy and error-prone
Solution Approach 1:
The patent applies universality by creating a unified configuration interface that handles multiple edge property scenarios through a single standardized API. Instead of requiring separate detailed parameters for each property, the system provides universal options (merge, keep, drop) that work across all edge properties, reducing API complexity while maintaining precise control capabilities.
Solution Approach 2:
The patent implements partial action by allowing users to specify only the properties they want to control explicitly, while leaving other properties to default behavior. This selective specification reduces the number of parameters users must provide, making the API less unwieldy while still enabling precise control over critical properties when needed.
Data Source
AI summary
Techniques are provided for strategy-based graph simplification. In an embodiment, a computer provides configurable strategies that simplify edges of a graph. A client selects and configures a strategy subset of the configurable strategies to define a particular simplification scheme. The computer simplifies a graph by applying the strategy subset to the graph. In embodiments, predefined classes or other application programming interface (API) is provided to clients to obtain and customize strategy instances, such as with a factory or builder. Strategy instances may be imperative or declarative. A service implementation, such as a graph engine, may be embedded or remoted. Techniques herein provide for reuse and optimization.