Text Filtering System Using Semantic Keywords and Logical Operators
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Solution Overview
Problem
Current text filtering methods based on basic keyword matching are inadequate as they fail to accurately identify the context and intent of text, leading to low identification accuracy and misreporting of information, such as mistreating valid texts that include filtering keywords in combination with other words.
Innovation Solution
A method and system for text filtering that uses pre-defined semantic keywords comprising basic keywords and logical operators to conduct semantic matches, allowing for the consideration of semantics in the entire text, thereby increasing filtering accuracy and reducing misreporting. The system stores basic keywords in a tree-type structure for efficient searching and includes a dictionary for character conversion to improve processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If basic keyword matching technology is used for text filtering, then the filtering process is simple and fast, but the identification accuracy rate is low and misreporting occurs
Solution Approach 1:
The patent segments the keyword matching process into two distinct stages: first, rapid basic keyword matching to identify potential matches, and second, semantic analysis to verify the actual meaning and context. This segmentation allows the system to maintain high processing speed through efficient keyword indexing while improving accuracy through subsequent semantic evaluation of the matched content.
Solution Approach 2:
The patent introduces semantic analysis as an intermediary step between basic keyword matching and final filtering decisions. This intermediary layer analyzes the contextual meaning, grammatical structure, and semantic relationships of the matched keywords within the text, thereby reducing false positives while maintaining the efficiency of the initial keyword-based approach.
2Device complexity
If basic keyword matching is applied, then the filtering system is simple to implement, but it cannot determine author position or attitude reflected in the text
Solution Approach 1:
The patent performs preliminary semantic analysis on the text content before making final filtering decisions. By pre-processing the text to extract semantic features, author position, and attitude indicators, the system preserves contextual information that would otherwise be lost in simple keyword matching, enabling more accurate and nuanced filtering outcomes.
3Measurement precision
If semantic matching with logical operators is implemented, then filtering accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent implements a dynamic filtering system that adapts its processing depth based on the complexity of the query and the characteristics of the text. For simple keyword matches with clear semantic meaning, the system performs rapid filtering. For more complex cases involving multiple logical operators or ambiguous contexts, the system dynamically increases the depth of semantic analysis, thereby balancing accuracy improvement with processing efficiency.
Data Source
AI summary
The present disclosure discloses a method and system for text filtering. The method for text filtering comprises: pre-defining a semantic keyword in a text filtering system, the semantic keyword comprising at least one basic keyword and one logical operator; after obtaining an input text, finding, by the text filtering system, the basic keyword constituting the semantic keyword in the input text according to the pre-defined semantic keyword; in an event that a text content matching the at least one basic keyword in the input text is found, further conducting a semantic match in the found text content, the semantic match further comprising matching the found text content with the semantic keyword according to the logical operator constituting the semantic keyword; and in an event that the semantic match is successful, filtering the matched text context.