Multi-Domain Information Matching Using AI Feature Extraction
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Solution Overview
Problem
Existing information retrieval methods face accuracy issues due to reliance on short document titles, which only contain a small portion of key content, leading to inadequate matching between user queries and documents.
Innovation Solution
A method and apparatus using artificial intelligence to evaluate the matching degree of multi-domain information by obtaining valid words and their expressions in queries and documents, generating context-based word expressions, and calculating matching features across information domains to determine a comprehensive matching score.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only the title of the document is used to calculate matching degree score, then the calculation process is simple and fast, but the accuracy of determining whether the document is matched with the query deteriorates because the title is short and contains only a small portion of key content
Solution Approach 1:
The patent divides the document into multiple information domains (title, abstract, content, keywords) and processes each domain separately through word segmentation and feature extraction. This segmentation allows the system to handle large documents efficiently while capturing comprehensive information, resolving the contradiction between accuracy and complexity.
Solution Approach 2:
The patent transforms the matching evaluation from a single-dimensional title-only approach to a multi-dimensional approach by extracting features from multiple information domains (title, abstract, content, keywords). Each domain contributes different dimensional information, enabling comprehensive matching while maintaining computational efficiency through structured processing.
2Measurement precision
If multi-domain information is processed to improve matching accuracy, then the accuracy of information retrieval is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary word segmentation and feature extraction for each information domain before the final matching calculation. By pre-processing the text data into structured feature representations, the system reduces computational overhead during the actual matching process, thereby decreasing overall processing time while maintaining high accuracy.
Solution Approach 2:
The patent applies different processing strategies to different information domains based on their local characteristics. The title domain receives different processing treatment compared to the content domain, optimizing the processing effort for each domain's specific contribution to matching accuracy. This localized processing approach reduces unnecessary computational overhead.
Data Source
AI summary
The present disclosure provides a method and apparatus for evaluating a matching degree of multi-domain information based on artificial intelligence, a device and a medium. The method comprises: respectively obtaining valid words in a query, and valid words in each information domain in at least two information domains in a to-be-queried document; respectively obtaining word expressions of valid words in the query and word expressions of valid words in said each information domain in at least two information domains in the to-be-queried document; based on the word expressions, respectively obtaining context-based word expressions of valid words in the query and context-based word expressions of valid words in said each information domain; generating matching features corresponding to said each information domain according to the obtained information; determining a matching degree score between the query and the to-be-queried document according to the matching features corresponding to said each information domain.