Social Network Data Reconciliation via Incremental Subnetwork Updates
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Solution Overview
Problem
Existing social networks often contain obsolete and inaccurate information, leading to faulty decision-making due to the lack of real-time updates and reconciliation of data regarding connections and relationships between entities.
Innovation Solution
A method and system that receive updated information, determine its effect on existing social network data using automated reasoning, and incrementally update the network in real-time, ensuring accuracy and validity of the information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If social network data is updated in real-time using automated reasoning and incremental updates, then the accuracy and reliability of network information is improved, but the computational complexity and processing time required increases
Solution Approach 1:
The patent segments the social network into subnetworks and updates them incrementally rather than reconstructing the entire network. This division allows real-time updates to be processed in smaller, manageable portions, reducing computational complexity while maintaining accuracy through localized reasoning about affected nodes and relationships.
Solution Approach 2:
The system performs preliminary actions by pre-establishing the network structure, node relationships, and connection patterns before real-time updates occur. This preliminary framework enables automated reasoning engines to quickly assess the impact of new information without starting from scratch, thereby improving reliability while controlling processing demands.
2Reliability
If comprehensive data reconciliation is performed to eliminate inaccurate information, then the validity of network data is improved, but the time and computational resources required increase
Solution Approach 1:
The patent implements feedback mechanisms where the automated reasoning engine continuously monitors network data for inconsistencies and validates new information against existing relationships. This ongoing feedback loop ensures data validity by detecting and correcting inaccuracies in real-time without requiring periodic comprehensive reconciliations, thus maintaining reliability while reducing time loss.
Solution Approach 2:
Rather than performing exhaustive data reconciliation on the entire network, the system applies partial action by focusing validation and reasoning efforts only on specific subnetworks and nodes affected by new information. This targeted approach maintains data validity through sufficient verification while minimizing the time and resources spent on processing.
3Adaptability or versatility
If the social network structure is dynamically updated to reflect new relationships and connections, then the adaptability of the network is improved, but the stability of existing network structures may be compromised
Solution Approach 1:
The patent applies dynamics by enabling the social network structure to adapt and change in response to new information while maintaining operational stability. The automated reasoning engine dynamically updates node attributes, relationships, and subnetwork configurations based on validated input, allowing the network to evolve and incorporate new connections without disrupting the overall structural integrity of established relationships.
Data Source
AI summary
A method of providing real-time information regarding objects in a social network includes receiving updated information regarding the social network, and determining, by a processor, an effect of the updated information on a set of existing social network information. The method also includes incrementally updating, by a processor, the set of existing social network information, and providing the updated set of social network information.