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研究生:張晏嘉
研究生(外文):Yen-Chia Chang
論文名稱:建構XML多維度資料區間索引之研究
論文名稱(外文):The Study of Indexing Strategy on XML-based Temporal Data
指導教授:邱紹豐邱紹豐引用關係
指導教授(外文):Andy S. Chiou
學位類別:碩士
校院名稱:大葉大學
系所名稱:資訊工程學系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2004
畢業學年度:95
語文別:中文
論文頁數:55
中文關鍵詞:時序性資料貪婪演算法
外文關鍵詞:Temporal dataXMLGreedy Algorithm
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隨著電子資訊化的潮流,時序性資料(Temporal Data)被廣泛地利用與研究,其儲存以及索引結構一直是學者們探討研究的重點。而XML(eXtensible Markup Language)為近年來新興的資料儲存和交換標準,由於XML文件內容的標籤元素與通訊協定獨立,使得XML文件特別適合在網際網路和全球資訊網的環境中流通傳輸。有別以往傳統資料庫管理系統(Database Management System, DBMS),XML的眾多特性讓資料更容易交流溝通,因此有越來越多資料嘗試以XML文件來儲存。
在利用XML文件作為時序性資料的儲存架構下,檢索資料必須一一比對文件中每筆資料,使得時序性資料於XML上之檢索相當耗時。而目前眾學者們對時序性資料儲存在XML文件上所提出的索引架構,雖然能夠提高資料檢索的效率,但由於在資料分群上只考量單一屬性,故只能提高單方面的檢索效率,無法提供全面性的效能提升。
因此,作者在本文提出一個以提高全方面檢索效能為目標之分群方法,藉由將時序性資料建構於多維度矩陣上,由資料於矩陣上之分布情況,考量所有屬性之方式將矩陣分割成多個區塊,並且利用貪婪演算法(Greedy Algorithm)的特性,來提高資料分群的速度。透過考量所有屬性來分群資料的方式,以得到全方面檢索效能提升之效益。
The temporal data is widely utilized and studied. The researchers are interested in the storage management and indexing technique on this special type of data. XML is a newly developed data structure and exchange standard in recent years. Because of its flexible structure of the XML document and independent communication protocol, XML document is especially suitable for transmitting on the internet network and World Wide Web. Different from the traditional database management systems, the numerous characteristics of XML make the data easier to exchange and communicate. As a result, more data are stored in XML format.
If the temporal data stored in XML structure, searching data must check for each data of document, which results in high cost. For temporal data, the traditional indexing techniques considered only single attribute in data clustering, making it faster to retrieve data by the indexed attribute. However, the efficiency declines dramatically when the search criteria is not indexed.
In our research, we proposed a new data clustering method for improving comprehensive efficiency of data retrieval. By building the temporal data in the multidimensional matrix observes the relation among the data. Then, we try to cut matrix apart into a lot of blocks by considering all attributes and utilized the characteristics of greedy algorithm to improve the speed of the data clustering. By this approach, we can improve comprehensive efficiency of data retrieval.
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授權書.............................................iii
中文摘要............................................iv
英文摘要............................................v
誌謝...............................................vi
目錄...............................................vii
圖目錄.............................................ix
表目錄.............................................xi

第一章 緒論.......................................1
1.1 研究動機...................................1
1.2 研究目的...................................3
1.3 論文結構...................................4
第二章 相關研究....................................5
2.1 XML.......................................5
2.2 時序性資料.................................7
2.3 時序性資料庫................................8
2.4 以XML儲存時序性資料.........................12
2.5 分群方式...................................15
2.6 索引架構...................................17
第三章 設計方法....................................22
3.1 分群策略...................................22
3.2 分群方法...................................26
第四章 實驗評估....................................36
4.1 測試環境...................................36
4.2 效能評估...................................38
第五章 結論與未來工作...............................42

參考文獻............................................44
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