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  • 學位論文

XBRL之案例資料庫設計與管理

An XBRL Instance DBMS Design

指導教授 : 盧以詮
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摘要


隨著現今網路科技的發展,企業彼此間的資訊流通變為更加快速與透明,而各企業間接採用自身所發布的格式與檔案,企業間並無統一的規格,造成企業商業資訊彼此間流通的困難度,所以出現了國際XBRL組織訂定了可延伸商業報告語言(eXtensible Business Reporting Language,XBRL),其所採用的技術是以XML技術所做的延伸,且為了保持其格式上的統一,採用的發展架構必須遵守三個階段,第一階段:制定技術規格標準(Specification)階段;第二階段:建立分類標準(Taxonomy)階段;第三階段:編制案例文件(Instance Document)階段。而其文件上的處理不同於以往的一般企業資訊報告,以往的企業資訊大多是以關聯式的邏輯架構為儲存基礎。而可延伸商業報告語言其邏輯架構出發點是以XML為概念,故其邏輯架構屬於樹狀結構,不同以往企業報告的儲存格式。故本研究的目的將探討XBRL文件儲存方式的差異評估與比較,並擇一較佳的方法去實作此XBRL案例資料庫管理系統。

關鍵字

XML XBRL 分類標準 案例文件

並列摘要


Recently, with the development in internet applications, the information flow between enterprises becomes even faster and more transparent. Enterprises are now indirectly adopting their self-developed file types and formats. There is no standard format among the enterprises, which causes a difficulty of business information sharing in between. Therefore an eXtensible business reporting language, XBRL, is formed by the international XBRL organization. The technology applied is based on XML, with extends. For the format to be in a consistently standard, the developing structure has to go through three critical stages. The first stage is to set up a technical specification; the second stage is to set up taxonomy; and the third stage is to develop instance documents. In the past, the enterprise information is based on relational data model and stored in a RDBMS, while the eXtensible business reporting language is based on the XML concept. The structure is therefore in a tree-view, which differs to the relational data model. This research therefore aims to study the differentiation of storing structure, and so as to develop a XBRL Instance database management system.

並列關鍵字

XML XBRL taxonomy Instance Document

參考文獻


[10] 王為孝,盧以詮教授,金融時間序列資料管理-模式、技術與建置,
[1] Yi-Chuan Lu, Hilary Cheng, Calvin Hsu, “FKMS: A Knowledge
[2] Hilary Cheng, Yi-Chuan Lu, Smile Wang “Approaching a Knowledge
[3] Yi-Chuan Lu, Hilary Cheng, “An Ontology-based Data Mining Approach in a Financial Knowledge Management System“, Third International Workshop on E-Business (Web 2004), 12/2004, pp 215-221.
Discovery Process for Corporate Bond Classifications via Neural Clustering Technique”, Proceedings of the International Conference on Artificial Intelligence, IC-AI2001, Volume III, 2001, p p1290 -1296.

被引用紀錄


吳季宓(2008)。XBRL導入銀行徵授信業務之應用〔碩士論文,元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-2407200814374100
黃志軒(2008)。以XML DB為基礎建構XBRL文件分析器〔碩士論文,元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-0807200818025700
鄭又逞(2008)。XBRL 於財務報表上的應用〔碩士論文,元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-2407200816535700
徐士超(2008)。XBRL與銀行信用風險之研究〔碩士論文,元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-0807200817154800

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