Dynamic Network Adaptation for Accurate Chatbot Request Routing
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Solution Overview
Problem
Conventional chatbots using fixed networks often fail to handle all user requests correctly, leading to paths that do not reach target nodes and necessitating human intervention, thereby undermining efficiency gains.
Innovation Solution
A computer-implemented method for adapting a network by modifying identifiers, associations, adding or removing nodes/connections, and using trained models to select nodes based on user inputs, ensuring paths reach target nodes and improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed network structure is used in a conventional chatbot, then the chatbot avoids hallucinations and inaccuracies, but it cannot handle all user requests correctly and requires human intervention
Solution Approach 1:
The patent implements a dynamic network structure that automatically adapts to user inputs by adding new nodes and connections. The system monitors user interactions and modifies the network topology in real-time, transforming the static conventional network into a dynamic structure that evolves with usage patterns. This allows the chatbot to maintain reliability while gaining adaptability to handle diverse user requests.
Solution Approach 2:
The system changes the parameters of the network structure by adding new nodes, modifying connections, and adjusting the topology based on user interaction data. This parameter modification enables the network to expand its capability to handle various user requests while maintaining the structured approach that prevents hallucinations.
2Reliability
If a fixed network structure is used, then the chatbot operates within set boundaries, but some user paths do not reach target nodes and efficiency is reduced
Solution Approach 1:
The network structure performs self-service by automatically monitoring its own performance and adapting its topology based on user interaction patterns. The system self-modifies by adding nodes and connections that address gaps in user request handling, thereby improving productivity while maintaining operational consistency without requiring external intervention.
Solution Approach 2:
The system implements feedback mechanisms that monitor user paths and identify when paths fail to reach target nodes. This feedback drives automatic network adaptation by adding necessary nodes and connections to ensure all user requests can be properly routed, thereby improving efficiency while maintaining reliability.
3Reliability
If human intervention is required for paths not reaching target nodes, then accuracy is maintained, but efficiency gains from chatbot automation are undermined
Solution Approach 1:
The system performs preliminary actions by proactively adding nodes and connections to the network based on anticipated user requests and patterns. By preparing the network structure in advance with potential future needs, the system prevents the need for human intervention before it occurs, thereby maintaining accuracy while eliminating time loss to human operator involvement.
Data Source
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Figure 1B~1C
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AI summary
There is provided a computer-implemented method for adapting a network. The network may comprise a plurality of network nodes, at least one network connection, and at least one identifier. Each network connection connects two network nodes. At least one of the network nodes may be a target node. Each identifier may be associated with at least one of the network nodes. A path taken by a user through the network comprises at least one of the network nodes. The network nodes comprised in the path may be selected base don comparing at least one user input with data pertaining to the at least one identifier. The computer-implemented method may comprise receiving data representative of network nodes comprised in the path. The method may comprise determining, based on the data, whether the path comprises at least one target node. If the path does not comprise at least one target node, the method may comprise adapting the network.