Dialog Data Collection System with Background Knowledge Provision

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Solution Overview

Problem

Collecting dialog data is difficult and expensive due to the need for large amounts of specific data, such as text, audio, and video, which is challenging to obtain legally and efficiently, especially for AI systems that require extensive data sets.

Innovation Solution

A method and device for collecting dialog data that involves acquiring features of a dialog subject selected by users, providing background knowledge information based on these features, and initiating dialog data collection tasks, with features like preset dialog subjects, knowledge information acquisition, and data saving mechanisms to facilitate efficient data collection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If dialog data is collected from Internet sources, then data variety is improved, but legal compliance difficulty and cost increase

Engineering Contradiction:

Improvedata varietyVSAvoidlegal compliance difficulty

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The system enables users to autonomously collect dialog data through predefined subjects and automatic knowledge information provision, eliminating the need for manual Internet data gathering and reducing legal compliance risks

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system introduces an intermediary platform that manages data collection between users and AI models, providing structured dialog subjects and knowledge information that replace direct Internet scraping while ensuring legal compliance

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of manufacture

If manual programming methods are used for AI systems, then system implementation is achieved, but data acquisition cost and complexity increase

Engineering Contradiction:

Improvesystem implementationVSAvoiddata acquisition complexity

Core Design Contradiction:

Ease of manufactureVSDevice complexity

Solution Approach 1:

The system uses predefined dialog subjects and templates as reusable copies that can be repeatedly applied across different AI training scenarios, eliminating the need for custom data collection programs for each project

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system creates a universal data collection framework that handles multiple dialog subjects and knowledge domains through a single platform, reducing both implementation effort and complexity compared to specialized manual approaches

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Reliability

If extensive data sets are collected for AI training, then model training effectiveness is improved, but data collection cost and time increase

Engineering Contradiction:

Improvemodel training effectivenessVSAvoiddata collection time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by pre-defining dialog subjects and preparing knowledge information databases before actual data collection begins, enabling users to quickly generate training data without extensive manual gathering

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system provides feedback mechanisms where knowledge information is automatically provided to users based on their dialog subject selections, guiding them to generate high-quality training data more efficiently and reducing iterative collection time

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20240046116A1Method and Device for Collecting Dialog Data

Publication Date: 2024.02.08 BEIJING XIYU JIZHI TECH CO LTD

AI summary

A method relates to collecting dialog data between two users and assisting users in collecting dialog data includes acquiring a feature of a dialog subject of a first dialog, acquiring, according to the feature or according to the feature and dialog data received from the two users, first knowledge information, and providing, based on the first knowledge information, background knowledge related to the first dialog to the two users.