초록
영어
The growing complication of regulations requires intelligent regulation management system, with support of information technology. In this research, we develop basic technology for analyzing rules and policies expressed in natural languages, in order to extract the regulatory attributes and automate data input process for regulation database. We analyze the frequency of verbs occurring in the regulation database, and focus on the most frequent types of regulations: ‘should submit,’ ‘should issue,’ and ‘may not’. Regex based approach and syntactic analysis approach are used for sentence structure analysis.
목차
Abstract
1. Introduction
2. Related Research
3. Regulation Attributes
4. Statistics of Regulation Texts
5. Grammatical Structure of Regulations
5.1 Analysis of “should submit” type sentence
5.2 Analysis of Example “Should Issue” Type Sentence
5.3 Analysis of Example “May Not” Type Sentence
6. Regex Based Approach
6.1 Regulation templates
6.2 Performance of Regex based approach
6.3 Remarks on Regex Based Approach
7. Syntactic Analysis Approach
7.1 POS tagging
7.2 Syntactic Analysis Procedure
7.3 Structure analysis
7.4 Performance of Syntactic Analysis Approach
7.5 Remarks on Syntactic Analysis Approach
8. Conclusion
REFERENCES
1. Introduction
2. Related Research
3. Regulation Attributes
4. Statistics of Regulation Texts
5. Grammatical Structure of Regulations
5.1 Analysis of “should submit” type sentence
5.2 Analysis of Example “Should Issue” Type Sentence
5.3 Analysis of Example “May Not” Type Sentence
6. Regex Based Approach
6.1 Regulation templates
6.2 Performance of Regex based approach
6.3 Remarks on Regex Based Approach
7. Syntactic Analysis Approach
7.1 POS tagging
7.2 Syntactic Analysis Procedure
7.3 Structure analysis
7.4 Performance of Syntactic Analysis Approach
7.5 Remarks on Syntactic Analysis Approach
8. Conclusion
REFERENCES
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보