Automated QA Training Using Forum Answer Keys

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Solution Overview

Problem

Training question answering (QA) systems requires vast amounts of time and expert resources due to the need for hand-built answer keys, which are domain-specific and labor-intensive.

Innovation Solution

Automatically training a QA system using answer keys derived from forum content, where questions are selected and answers are identified from crowd-based sources with a confidence level above a threshold, creating an answer key for system training.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If hand-built answer keys are used for training QA systems, then training accuracy and reliability are improved, but time consumption and resource requirements increase significantly

Engineering Contradiction:
Improvetraining accuracyVSAvoidtime consumption
Core Design Contradiction:
ReliabilityVSLoss of time

Solution Approach 1:

The patent creates answer keys by automatically copying and extracting information from existing forum Q&A pairs and knowledge base documents, rather than hand-building each answer key. This automated copying process maintains accuracy while dramatically reducing the time and expert resources required for training data preparation

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The system performs self-service by automatically generating answer keys from existing knowledge base content without requiring expert intervention. The automated pipeline extracts questions, identifies candidate answers, and creates training data independently, eliminating the need for manual expert curation while maintaining training quality

Inventive Principle:
Principle #25Self-service

2Reliability

If expert resources are used to hand-build answer keys, then domain expertise and answer quality are improved, but cost and complexity increase

Engineering Contradiction:
Improveanswer qualityVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces the mechanical process of expert manual answer key creation with an automated computational system. Natural language processing algorithms, information retrieval systems, and automated scoring mechanisms substitute for human experts, reducing system complexity while maintaining answer quality through consistent, scalable automation

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

3Reliability

If vast amounts of training data are manually created, then model performance and accuracy are improved, but productivity and scalability worsen

Engineering Contradiction:
Improvemodel performanceVSAvoidtraining efficiency
Core Design Contradiction:
ReliabilityVSProductivity

Solution Approach 1:

The patent performs preliminary action by pre-processing and structuring knowledge base content into question-answer pairs before they are needed for training. This advance preparation creates a ready-to-use training data pipeline that can rapidly generate answer keys when needed, improving both model performance and training efficiency

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system maintains continuity of useful action by implementing an automated, continuous pipeline for answer key generation. Rather than intermittent manual creation, the system continuously extracts, processes, and validates training data from knowledge base sources, ensuring steady production of high-quality training materials without interruption or manual intervention

Inventive Principle:
Principle #20Continuity of useful action

Data Source

PatentUS9626622B2Training a question/answer system using answer keys based on forum content
Publication Date: 2017.04.18 INTERNATIONAL BUSINESS MACHINE CORPORATION
  • US9626622B2 patent drawing
  • US9626622B2 patent drawing
  • US9626622B2 patent drawing

AI summary

An approach is provided to train a question answering (QA) system using answer keys based on forum content. In the approach, a question is selected from a post in a threaded discussion. An answer to the selected question is automatically identified from crowd-based sources, with the identified answer having a confidence level greater than a threshold. An answer key is built using the selected question and the identified answer. The QA system is automatically trained using the answer key.