Morpheme Analysis with Syntax Dependency Indexing
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Solution Overview
Problem
Existing text analysis systems are inefficient in extracting meaning contents from natural language texts due to the complexity of rule application processes, which do not adequately consider the dependency structure between clauses, leading to prolonged processing times.
Innovation Solution
A text analysis system that decomposes input text into morphemes, sets pre-tags using attribute dictionaries, identifies dependency relationships, generates an index for rapid rule application, and applies determination rules to attribute tags, enabling efficient extraction of meaning and sentimental attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of rules are applied to the syntax tree in a predetermined order to extract meaning contents, then the extraction accuracy is improved, but the processing time is prolonged
Solution Approach 1:
The patent applies certain determination rules at the morpheme analysis stage before syntax tree construction is complete. By performing preliminary extraction of meaning contents that can be determined from morpheme sequences alone, the system reduces the number of rules that need to be applied to the full syntax tree, thereby decreasing processing time while maintaining extraction accuracy
Solution Approach 2:
The patent divides the rule application process into two segments: (1) rules applicable at the morpheme analysis stage without requiring complete syntax tree structure, and (2) rules applicable after syntax analysis. This segmentation allows parallel processing and reduces the sequential processing burden, improving efficiency without sacrificing accuracy
2Loss of time
If rules are applied at the morpheme analysis stage without referring to the syntax tree, then the determination time is reduced, but the number of applicable rules is limited
Solution Approach 1:
The patent implements a dynamic rule application strategy where the system adaptively selects which rules to apply at which stage based on the text structure. Rules that can be applied early are executed at morpheme analysis, while more complex rules requiring syntactic context are applied after syntax analysis, optimizing both speed and comprehensiveness
3Measurement precision
If the dependency structure between clauses is considered to accurately extract meaning contents, then the extraction accuracy is improved, but the processing complexity increases
Solution Approach 1:
The patent performs preliminary identification of clauses and their dependency relationships during morpheme analysis, before applying all determination rules. This preliminary structuring reduces the complexity of subsequent rule application by having the syntactic framework already in place, allowing accurate extraction without excessive processing complexity
Data Source
AI summary
A morpheme analysis unit sets beforehand a meaning-candidate tag and a sentimental theme tag for a morpheme required to be input as a text. A syntax analysis unit generates an index where a clause including a meaning-candidate tag and a sentimental theme tag and a type of each tag. A meaning attribute extraction unit recognizes a clause including a meaning-candidate and a type of tag with reference to the index, and then applies a meaning attribute rule, sets a meaning attribute tag for a necessary clause, and updates the index. A sentimental analysis unit also recognizes a clause including a sentimental theme tag and a clause including a meaning attribute tag with reference to the index, and then applies a sentimental analysis rule and sets a sentimental attribute tag for a necessary clause.