Chatbot Knowledge Base Lifecycle Management

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing chatbot systems face challenges in managing knowledge base updates, version control, and error resolution, particularly for non-technical service owners who struggle with parsing questions, defining dialog flows, and handling failures during system operation.

Innovation Solution

Implementing model lifecycle management (MLM) in chatbot systems, which includes a method for managing the lifecycle of a knowledge base by receiving update requests, performing tests, and submitting new versions, allowing service owners to easily manage and update knowledge points and knowledge bases without requiring extensive technical expertise.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If a chatbot system implements manual knowledge base management processes, then service owners can update knowledge points, but the process becomes complex and difficult to operate

Engineering Contradiction:

Improveease of knowledge base managementVSAvoidcomplexity of management process

Core Design Contradiction:

Ease of operationVSDevice complexity

Solution Approach 1:

The patent segments the knowledge base management process into distinct lifecycle stages: development environment (current version), test environment (submit version), and production environment (production version). Each stage has specific operations and transitions, simplifying the overall complex management process by breaking it down into manageable, standardized steps that service owners can follow easily.

Inventive Principle:

Principle #1Segmentation

2Productivity

If the chatbot system allows quick updates to knowledge bases, then responsiveness to client requirements improves, but system stability and reliability may deteriorate

Engineering Contradiction:

Improvespeed of knowledge base updatesVSAvoidsystem stability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent implements preliminary testing actions in the test environment before deploying updates to production. The system requires creating a submit version in the test environment, performing necessary tests, and only after successful testing does it allow promotion to the production environment. This preliminary validation ensures system stability while maintaining update speed.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent creates a buffer zone through the test environment and version control mechanisms. Before updates reach production, they undergo testing in the submit version, and the system maintains the ability to rollback if issues arise. This cushioning mechanism protects system reliability while enabling quick updates.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

3Measurement precision

If the chatbot system implements version control and testing procedures, then error detection improves, but the time required for knowledge base updates increases

Engineering Contradiction:

Improveerror detection capabilityVSAvoidupdate time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent implements automated testing and validation mechanisms that perform error detection without requiring extensive manual intervention. The system automatically manages version transitions, performs necessary validations, and maintains test cases, reducing the time overhead while improving error detection capability.

Inventive Principle:

Principle #25Self-service

4Adaptability or versatility

If the chatbot system maintains multiple versions of knowledge bases, then ability to revert to previous versions improves, but system complexity increases

Engineering Contradiction:

Improveversion rollback capabilityVSAvoidcomplexity of version management

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments version management into distinct, standardized lifecycle stages (current, submit, production versions) with defined transitions between them. This segmentation provides clear rollback paths while maintaining simplicity through standardized processes rather than allowing arbitrary version management.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11501211B2Chatbot system with model lifecycle management

Publication Date: 2022.11.15 HONG KONG APPLIED SCI & TECH RES INST

AI summary

The present disclosure describes methods, devices, and non-transitory computer readable storage medium for managing lifecycle of a knowledge base (KB) in chatbot systems. The method includes receiving an update request and updating a current-version KB as a new current-version KB. The method also includes receiving a first test request from a knowledge point (KP) operator and determining whether the new current-version KB passes a first test; and in response to the determination that the new current-version KB passes the first test, submitting the new current-version KB as a new submit-version KB. The method further includes receiving a second test request from a KP manager and determining whether the new submit-version KB passes a second test; and in response to the determination that the new submit-version KB passes the second test, storing an original production-version KB as a pervious-version KB and submitting the new submit-version KB as a new production-version KB.