XANDY: Detecting Changes on Large Unordered XML Documents using Relational Databases

Abstract

Previous works in change detection on XML documents are not suitable for detecting the changes to large XML documents as it requires a lot of memory to keep the two versions of XML documents in the memory. in this paper, we take a more conservative yet novel approach of using traditional relational database engines for detecting the changes to large unordered XML documents. We elaborate how we detect the changes on unordered XML documents by using relational database. to this end, we have implemented a prototype system called XANDY that converts XML documents into relational tuples and detects the changes from these tuples by using SQL queries. Our experimental results show that the relational approach has better scalability compared to published algorithms like X-Diff. the result quality of our approach is comparable to the one of X-Diff. © Springer-Verlag Berlin Heidelberg 2005.

Department(s)

Computer Science

International Standard Serial Number (ISSN)

0302-9743

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 Springer, All rights reserved.

Publication Date

01 Jan 2005

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