On-Demand Collaboration Network Graphs for Reducing Code Effort
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Solution Overview
Problem
Current collaboration systems face challenges in reducing the code development effort required to deliver new collaboration activity insights to users, as the specialized nature of code development presents barriers to generating and presenting new insights effectively.
Innovation Solution
Implementing a framework that facilitates on-demand generation of collaboration network graphs from high-order configuration documents, using a graph service that maintains real-time collaboration network graphs and processes feed requests to produce entity-specific collaboration feeds, with API integration and behavior overlay modules to customize graph and feed definitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If new code is developed to capture and present newly-demanded collaboration insights, then new collaboration activity insights can be delivered to users, but code development effort and system complexity increase significantly
Solution Approach 1:
The system segments the collaboration insight delivery into modular components: event capture modules that collect collaboration events, graph generation modules that process events into network graphs, and feed presentation modules that display insights. This modular architecture allows new insights to be added by configuring existing modules rather than developing new code, reducing code development effort while maintaining adaptability.
Solution Approach 2:
The patent implements universal graph generation algorithms and feed presentation frameworks that can handle multiple types of collaboration events and insights through a single codebase. The system uses configurable parameters and templates to adapt the same underlying infrastructure to different insight requirements, eliminating the need for specialized code development for each new insight type.
2Loss of information
If more code is added to relate captured event information to user relationships and location, then newly-demanded insights can be delivered, but the specialized nature of code development creates barriers
Solution Approach 1:
The patent introduces intermediary modules that act as adapters between event capture and insight delivery. These intermediaries standardize the processing of diverse collaboration events into a unified format, making it easier to relate event information to user relationships and location without requiring specialized code for each event type. The intermediaries handle the complexity of information integration while maintaining ease of code development.
Solution Approach 2:
The system uses parameter-based configuration to adapt the same code to different information requirements. By changing parameters such as event types, relationship definitions, and location contexts, the system can deliver comprehensive collaboration insights without adding specialized code. This parameter-driven approach maintains ease of manufacture while capturing complete collaboration information.
3Ease of operation
If additional code is added to present insights in a manner that fosters human cognition, then user understanding improves, but code development barriers increase
Solution Approach 1:
The patent implements preliminary graph generation and feed preparation that structures collaboration insights in cognitively-friendly formats before presentation. The system pre-processes collaboration events into network graphs and organized feeds using standardized templates designed to foster human cognition. This preliminary structuring eliminates the need for complex presentation code while improving ease of operation, as the cognitive optimization is built into the template framework rather than requiring specialized development for each interface.
Data Source
AI summary
Systems and methods for on-demand generation of customizable collaboration network graphs. A method embodiment operates in a collaboration system that comprises content objects that are operated on by a plurality of users. Interactions with the content objects are detected and streamed into a customizable graph platform. Customization is accomplished by configuring the graph platform to gather particular events and corresponding data that pertain to the entity interaction events and/or to the users that raised the events. The graph platform organizes the data into data structures that codify a collaboration network graph, where the nodes of the collaboration network graph refer to customizable ones of the content objects and where the edges of the collaboration network graph refer to customizable parameters or values that characterize relationships between connected nodes of the collaboration network graph. Multiple behavior overlays can be applied to cause the customizable graph platform to process particular events differently.