AI Intention Analysis via Syntax Tree Qualifier Extraction
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Solution Overview
Problem
Current search engine technologies have limited recognition capabilities for user intentions, relying on simple templates and resulting in a narrow recognition range and imprecise classification of user queries.
Innovation Solution
A method and apparatus for analyzing user intentions using artificial intelligence, which involves receiving a query, acquiring a keyword through a preset strategy, and determining the intention by parsing the query with a syntax tree to identify qualifiers, thereby enhancing the precision and range of intention recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple templates are used for intention recognition, then the method is simple and easy to implement, but the recognition range is small and classification precision is low
Solution Approach 1:
The patent segments the intention recognition process into multiple stages: first extracting keywords from the query, then building a syntax tree to identify qualifiers, and finally determining the intention type based on the relationship between keywords and qualifiers. This segmentation allows the system to achieve high precision without requiring a single complex template to cover all cases.
Solution Approach 2:
The patent introduces a new dimension of analysis by utilizing the syntax tree structure of queries. Instead of relying solely on template matching, the system analyzes the grammatical structure and relationships between different components of the query, adding a structural dimension to the recognition process that significantly improves precision.
2Device complexity
If simple templates are used for intention recognition, then the implementation is straightforward, but the recognition field is limited
Solution Approach 1:
The patent creates a universal intention recognition framework that can handle multiple types of queries across different domains. The syntax tree-based approach is domain-agnostic and can adapt to various query structures, making the system versatile while maintaining a relatively simple implementation through standardized processing steps.
Solution Approach 2:
The system dynamically adapts to different query types by constructing syntax trees that reflect the specific structure of each query. This dynamic structure building allows the system to handle diverse query patterns without requiring pre-defined templates for each scenario, thereby expanding the recognition field.
3Ease of operation
If template-based methods are used, then the system is simple to operate, but the intention analysis accuracy is insufficient
Solution Approach 1:
The system performs self-service by automatically constructing syntax trees and identifying qualifiers without requiring manual template configuration for each query type. The algorithm autonomously analyzes the query structure and determines the appropriate intention classification, maintaining ease of operation while achieving high accuracy.
Data Source
AI summary
The present disclosure provides a method and an apparatus for analyzing an intention based on artificial intelligence. The method includes: receiving a query; acquiring a keyword of an intention of the query according to a preset strategy; acquiring a qualifier of the intention of the query according to the keyword based on a syntax tree; and determining the intention of the query according to the keyword and the qualifier.