資訊管理學報
蘇國瑋;許蒞彥;吳旻霙;黃博信;
頁: 111-141
日期: 2009/07
摘要: 一般法規草擬時在結構上及內容的安排上，最易發生錯誤的情形有以下三種：結構不完整是最常見的情形，它極易造成閱讀及檢索上的困擾。內容不一致也是另一常見的情形，使得前後的法規互相矛盾。術語不統一也是另一常見的情形，造成法規含混或模稜兩可的情形，導致使用者對法規原意的誤解或混淆。本研究探討如何運用索引典(Thesaurus)、UML(Unified Modeling Language)、OWL(Web Ontology Language)及人工智慧中的本體論技術，發展一決策支援平台，輔助教育行政法規的草擬。本研究分析教育行政法規的結構知識及語句關係，並應用索引典的編制技術將屬於自然語言的條文，以結構化的方式選擇詞彙和建立詞彙體系。利用UML建構一概念模式(Conceptual Model)，將半結構化的法規文件轉成結構化的圖形，呈現條文和條文間，以及法規和法規間的關連。應用本體論方法論(Ontology Methodology)，建立詞彙體系、法規條文間的關連，以Protégé為實作工具，整合為描述法規起草基本知識的OWL本體論知識庫。此系統的目的是在法規起草的過程中提供協助，避免一個法規內部各種規則之間以及新法規與現有法規之間的相互衝突，以改善制定法規上的效率及品質。
關鍵字: 人工智慧;本體論;教育行政法規;決策支援系統;
Abstract: Generally, during the process of drawing up regulation, one would find one of the three problems: structure of clauses is incomplete, content is inconsistent, terms are not unified. Regulations with these problems will lead to the puzzlement at later stage, and will prove very efficient. It is extremely troublesome for users to read and search with these problems in regulations, because they could cause the regulation to be ambiguous or equivocal, and could produce an irreconcilable conflict between regulations. It could also lead to user's misunderstanding or obscurity to the original meaning of the regulation. This research applies Thesaurus, UML, OWL and the Ontology to develop a decision support framework for assisting the development of educational administrative regulations. This research applies Ontology to analyze the knowledge concepts of the educational administrative regulation and identifies the relationship among regulation sentences. We use Thesaurus to build a classified hierarchy for knowledge items, UML to further modify the semi-structured regulations into a structural form, and Ontology to develop knowledge hierarchy of the structural form. The Ontology language which we use is OWL. The system is capable of assisting regulation developers to reduce those problems above.
Keywords: Artificial Intelligence;Ontology;Educational Administrative Regulation;Decision Support System;
瀏覽次數: 11586 下載次數: 1671
引用 導入Endnote
頁: 111-141
日期: 2009/07
摘要: 一般法規草擬時在結構上及內容的安排上，最易發生錯誤的情形有以下三種：結構不完整是最常見的情形，它極易造成閱讀及檢索上的困擾。內容不一致也是另一常見的情形，使得前後的法規互相矛盾。術語不統一也是另一常見的情形，造成法規含混或模稜兩可的情形，導致使用者對法規原意的誤解或混淆。本研究探討如何運用索引典(Thesaurus)、UML(Unified Modeling Language)、OWL(Web Ontology Language)及人工智慧中的本體論技術，發展一決策支援平台，輔助教育行政法規的草擬。本研究分析教育行政法規的結構知識及語句關係，並應用索引典的編制技術將屬於自然語言的條文，以結構化的方式選擇詞彙和建立詞彙體系。利用UML建構一概念模式(Conceptual Model)，將半結構化的法規文件轉成結構化的圖形，呈現條文和條文間，以及法規和法規間的關連。應用本體論方法論(Ontology Methodology)，建立詞彙體系、法規條文間的關連，以Protégé為實作工具，整合為描述法規起草基本知識的OWL本體論知識庫。此系統的目的是在法規起草的過程中提供協助，避免一個法規內部各種規則之間以及新法規與現有法規之間的相互衝突，以改善制定法規上的效率及品質。
關鍵字: 人工智慧;本體論;教育行政法規;決策支援系統;
The Development of an Administrative Regulations Support System with Artificial Intelligence: A Case with One University's Educational Administrative Regulations
Abstract: Generally, during the process of drawing up regulation, one would find one of the three problems: structure of clauses is incomplete, content is inconsistent, terms are not unified. Regulations with these problems will lead to the puzzlement at later stage, and will prove very efficient. It is extremely troublesome for users to read and search with these problems in regulations, because they could cause the regulation to be ambiguous or equivocal, and could produce an irreconcilable conflict between regulations. It could also lead to user's misunderstanding or obscurity to the original meaning of the regulation. This research applies Thesaurus, UML, OWL and the Ontology to develop a decision support framework for assisting the development of educational administrative regulations. This research applies Ontology to analyze the knowledge concepts of the educational administrative regulation and identifies the relationship among regulation sentences. We use Thesaurus to build a classified hierarchy for knowledge items, UML to further modify the semi-structured regulations into a structural form, and Ontology to develop knowledge hierarchy of the structural form. The Ontology language which we use is OWL. The system is capable of assisting regulation developers to reduce those problems above.
Keywords: Artificial Intelligence;Ontology;Educational Administrative Regulation;Decision Support System;
瀏覽次數: 11586 下載次數: 1671
引用 導入Endnote