Automated Topic Concept Mining via Part-of-Speech Filtering
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Solution Overview
Problem
Current topic concept mining technologies require significant labor costs due to the manual filtering of candidate topic concepts based on seed templates and queries, which is inefficient and time-consuming.
Innovation Solution
A method involving word segmentation and part-of-speech tagging of candidate topic concepts, followed by filtering based on preset thresholds of accurate and inaccurate concepts within their part-of-speech sequences, to automatically refine and extract relevant topic concepts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual filtering of candidate topic concepts is performed, then accuracy of topic concept mining is improved, but labor cost and time consumption increase
Solution Approach 1:
The patent replaces the manual filtering mechanism with an automated part-of-speech tagging system. The system automatically tags parts of speech for candidate topic concepts and uses these tags to filter inaccurate concepts, eliminating the need for manual review while maintaining high accuracy in topic concept mining.
Solution Approach 2:
The system performs self-service by automatically evaluating and filtering candidate topic concepts using part-of-speech tagging rules. The mining system itself conducts the filtering operation that would otherwise require human intervention, making the process autonomous and efficient.
2Measurement precision
If manual filtering of candidate topic concepts is performed, then accuracy of topic concept mining is improved, but labor cost increases
Solution Approach 1:
The patent replaces the manual filtering mechanism with an automated part-of-speech tagging system. The system automatically tags parts of speech for candidate topic concepts and uses these tags to filter inaccurate concepts, eliminating the need for manual review while maintaining high accuracy in topic concept mining.
Solution Approach 2:
The system performs self-service by automatically evaluating and filtering candidate topic concepts using part-of-speech tagging rules. The mining system itself conducts the filtering operation that would otherwise require human intervention, making the process autonomous and efficient.
3Ease of manufacture
If automated filtering based on part-of-speech sequence is performed, then labor cost is reduced, but complexity of processing increases
Solution Approach 1:
The patent segments the filtering process into discrete part-of-speech tagging steps. By breaking down the complex filtering task into manageable segments (tagging individual words, evaluating sequences, applying thresholds), the system reduces overall processing complexity while maintaining automation benefits.
Data Source
AI summary
The present disclosure provides a method, a device, an equipment and a storage medium for mining a topic concept. The method includes: acquiring a plurality of candidate topic concepts based on a query; performing word segmentation on the plurality of candidate topic concepts and performing part-of-speech tagging on words obtained after performing the word segmentation, to obtain a part-of-speech sequence of each of the plurality of candidate topic concepts; and filtering the plurality of candidate topic concepts based on the part-of-speech sequence, to filter out a topic concept corresponding to a target part-of-speech sequence among the plurality of candidate topic concepts, in which a proportion of accurate topic concepts in the target part-of-speech sequence is lower than or equal to a first preset threshold, or a proportion of inaccurate topic concepts in the target part-of-speech sequence is higher than or equal to a second preset threshold.