DocumentCode
2507175
Title
X-Diff: an effective change detection algorithm for XML documents
Author
Wang, Yuan ; DeWitt, David J. ; Cai, Jin-Yi
Author_Institution
Wisconsin Univ., Madison, WI, USA
fYear
2003
fDate
5-8 March 2003
Firstpage
519
Lastpage
530
Abstract
XML has become the de facto standard format for Web publishing and data transportation. Since online information changes frequently, being able to quickly detect changes in XML documents is important to Internet query systems, search engines, and continuous query systems. Previous work in change detection on XML, or other hierarchically structured documents, used an ordered tree model, in which left-to-right order among siblings is important and it can affect the change result. We argue that an unordered model (only ancestor relationships are significant) is more suitable for most database applications. Using an unordered model, change detection is substantially harder than using the ordered model, but the change result that it generates is more accurate. We propose X-Diff, an effective algorithm that integrates key XML structure characteristics with standard tree-to-tree correction techniques. The algorithm is analyzed and compared with XyDiff [CAM02], a published XML diff algorithm. An experimental evaluation on both algorithms is provided.
Keywords
XML; document handling; electronic publishing; query formulation; tree data structures; Internet query system; Web publishing; X-Diff; XML document; XML structure characteristic; continuous query system; data transportation; online information; ordered tree model; search engine; tree-to-tree correction technique; Algorithm design and analysis; Change detection algorithms; Databases; Detection algorithms; Electronic publishing; Internet; Search engines; Standards publication; Transportation; XML;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 2003. Proceedings. 19th International Conference on
Print_ISBN
0-7803-7665-X
Type
conf
DOI
10.1109/ICDE.2003.1260818
Filename
1260818
Link To Document