Semantic Indexing for Natural Language Question Answering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current natural language question-answering systems face low performance due to errors in linguistic analysis and the provision of unnecessary retrieval results, caused by misunderstandings of user intent and information requests.
Innovation Solution
A system and method that analyzes and indexes irregular documents by their meanings, using a combination of morpheme, lexical, syntax, and semantic analysis to extract index words from input questions, allowing for targeted searches in databases and providing accurate answers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If linguistic analysis results are used to search documents and extract answers, then the system can process natural language questions, but the performance is low due to errors in linguistic analysis
Solution Approach 1:
The patent introduces a semantic analysis layer as an intermediary between linguistic analysis and answer extraction. This semantic analysis layer uses knowledge graphs and semantic relationships to verify and correct linguistic analysis results, thereby improving answer accuracy while maintaining natural language processing capability
Solution Approach 2:
The system implements feedback mechanisms by using knowledge graphs to verify linguistic analysis results. The semantic relationships in the knowledge graph provide feedback to correct errors in linguistic analysis, creating a iterative improvement process that enhances reliability
2Productivity
If general information search methods are used to search original text or divided documents, then documents can be retrieved, but unnecessary results are provided causing performance degradation
Solution Approach 1:
The patent applies local quality by searching and retrieving only the specific portions of documents that are relevant to the question, rather than retrieving entire documents or all divided sections. The system uses semantic analysis to identify and retrieve only the local information needed, improving both speed and relevance
Solution Approach 2:
The system segments documents into meaningful units based on semantic analysis and knowledge graph relationships. This segmentation allows the system to retrieve only the relevant segments that answer the question, avoiding unnecessary results while maintaining efficient retrieval
Data Source
AI summary
Provided are a system and method for answering a natural language question which show improved information retrieval performance. The system includes an index unit configured to analyze text of previously stored irregular documents and classify and index the irregular documents according to meanings of sentences or paragraphs, a database configured to receive and store the irregular documents indexed according to the meanings and transmitted from the index unit, a retrieval unit configured to extract an index word by semantically analyzing an input question and search the database for documents related to the extracted index word, and a provision unit configured to generate a correct answer to the question by analyzing the documents searched by the retrieval unit and provide the search results and the correct answer.