Text Problem Mathematical Processing via Semantic Vector Encoding
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Solution Overview
Problem
Current methods for answering questions using artificial intelligence rely on preset expression templates, which are limited and result in low accuracy due to the diversity of questions, leading to inaccurate expressions.
Innovation Solution
A mathematical processing method that maps numerals in question text sequences to expression words, encodes the text into semantic vectors, and replaces expression words with mapped numerals to generate more accurate expressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If preset fixed expression templates are used to answer questions, then the processing method is simple, but the accuracy of question-answering is low due to limitations in template applicability
Solution Approach 1:
The patent transforms the static preset template system into a dynamic expression generation system. Instead of using fixed templates, the system dynamically generates mathematical expressions by encoding question text sequences into semantic vectors and decoding them into expressions that adapt to the specific question at hand, thereby improving accuracy while maintaining reasonable complexity
Solution Approach 2:
The patent changes the parameter representation from discrete template selections to continuous semantic vectors. By encoding questions into semantic vectors and using these vectors to guide expression generation, the system can capture subtle variations in question meaning that fixed templates cannot accommodate, thus improving answering accuracy
2Device complexity
If preset fixed expression templates are used to answer questions, then the system complexity is low, but the adaptability to diverse questions is limited
Solution Approach 1:
The patent creates a universal expression generation system that can handle diverse questions through a single encoding-decoding framework. The semantic vector representation serves as a universal intermediary that captures the essence of any mathematical question, allowing the system to generate appropriate expressions without requiring separate templates for different question types
Solution Approach 2:
The patent replaces the mechanical template-matching system with a semantic processing system. Instead of mechanically selecting from predefined templates based on keyword matching, the system uses semantic encoding and decoding to generate expressions that naturally adapt to the question content, significantly improving versatility
Data Source
AI summary
Embodiments of the present application disclose a mathematical processing method for a textual question, an apparatus, a computer device, and a computer storage medium. A numeral in a question text sequence is mapped to an expression word, a question text sequence including the expression word is encoded into a semantic vector, an expression is generated by using the semantic vector including question information, and the expression word in the expression is replaced with the mapped numeral, so that the obtained mathematical expression, compared with a preset fixed expression template, is more accurate, is more likely to meet question-answering requirements, and can improve intelligent question-answering accuracy.