Search-Query Question Generation for Sparse-Field Q&A
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Solution Overview
Problem
Existing information sharing services face challenges in providing relevant information to users in fields with few questions, leading to reduced user convenience.
Innovation Solution
An information processing apparatus that generates questions based on search queries, receives user answers, and provides information including the generated questions and answers, utilizing AI and machine learning to enhance user engagement and information relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users rely on existing question-answer databases for information retrieval, then information can be shared among users, but information desired by users in fields with few questions cannot be obtained
Solution Approach 1:
The system automatically generates questions based on search queries without requiring manual question creation by users or administrators. The question generation unit creates relevant questions from user search behavior, and the system autonomously builds the Q&A database through this self-service mechanism, resolving the contradiction between comprehensive information coverage and ease of use.
Solution Approach 2:
The system performs preliminary question generation based on search queries before users need the information. By anticipating user information needs through search pattern analysis and pre-generating relevant questions, the system ensures information availability in fields where questions are scarce, improving both adaptability and user convenience.
2Quantity of substance
If a Q&A service is provided based on existing questions only, then information sharing can occur, but the service is insufficient in fields where there are few questions
Solution Approach 1:
The system replaces the manual mechanical process of question creation with an automated question generation unit that creates questions algorithmically based on search queries. This substitution enables rapid expansion of the question database across diverse fields without requiring proportional increases in manual content creation resources, thereby improving field coverage while maintaining question quantity.
3Adaptability or versatility
If manual question creation is used to cover all fields, then comprehensive information can be provided, but the complexity and time required increases significantly
Solution Approach 1:
The system replaces time-consuming manual question creation with an automated question generation unit that processes search queries algorithmically. This substitution dramatically reduces the time required to create questions while maintaining comprehensive field coverage, as the automated system can generate multiple questions simultaneously from search pattern data without the sequential time constraints of manual creation.
Solution Approach 2:
The system changes the fundamental parameter of question creation from manual text input to automated generation based on search query analysis. By transforming the creation process from a time-intensive human activity to an automated computational process, the system achieves comprehensive information coverage across multiple fields without incurring proportional increases in time investment.
Data Source
AI summary
An information processing apparatus according to the present application includes a generation unit that generates a question based on a search query used for searching for web content, a reception unit that receives an answer by a user to the question generated by the generation unit, and a provision unit that provides information including the question generated by the generation unit and the answer received by the reception unit.