Automated Response Follow-Up System for Information Retrieval
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Solution Overview
Problem
Current information retrieval systems require users to manually generate follow-up queries to find related information, which can be inefficient and incomplete, as they do not automatically provide follow-up questions or responses based on user interactions.
Innovation Solution
A system that uses natural language processing to analyze user responses, generate follow-up questions, and pre-fetch responses from content providers, modifying the user interface to display these questions and responses, thereby automating the follow-up query process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users manually generate follow-up queries to find related information, then information retrieval completeness can be improved, but user time consumption and operational complexity increase
Solution Approach 1:
The system automatically generates follow-up queries and retrieves related information without requiring user intervention. The query generation module autonomously analyzes initial query results and formulates subsequent queries, while the information retrieval module automatically fetches additional relevant data, enabling the system to serve itself in completing information retrieval tasks.
Solution Approach 2:
The system pre-generates potential follow-up queries and pre-retrieves related information before users actually need it. By analyzing the initial query results and anticipating potential information gaps, the system prepares follow-up content in advance, so that when users need additional information, it is already available without requiring them to spend time formulating and executing manual follow-up queries.
2Loss of information
If users manually generate follow-up queries to locate further related information, then information retrieval completeness can be improved, but ease of operation deteriorates
Solution Approach 1:
The system autonomously performs the complete follow-up query generation and information retrieval process without requiring user operations. The query generation module automatically analyzes results and creates follow-up queries, while the information retrieval module automatically executes these queries and integrates results, eliminating the need for users to manually generate or manage follow-up queries.
3Productivity
If automated response follow-up is implemented using natural language processing, then productivity is improved, but device complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: a query generation module that analyzes results and generates follow-up queries, an information retrieval module that executes queries and fetches data, a natural language processing module that processes and understands query content, and a result integration module that combines results. This segmentation allows each module to specialize in specific tasks, improving overall efficiency while making the complex system more manageable through clear separation of concerns.
Data Source
AI summary
Aspects include generation of automated response follow-up. A response to a question from a user is received at a response follow-up system. The response follow-up system analyzes the response using natural language processing to identify one or more response terms. The response follow-up system generates one or more follow-up questions based on the one or more response terms. Based on the response, one or more follow-up responses to the one or more follow-up questions are pre-fetched from one or more content provider systems including one or more content servers, where a question answering system including the response follow-up system is communicatively coupled to the one or more content provider systems through a network. The response follow-up system modifies an aspect of a user interface displayed to the user based on the one or more follow-up questions and the one or more follow-up responses.