XML structural delta mining: issues and challenges

Authors:
Qiankun Zhao;Ling Chen;Sourav S. Bhowmick;Sanjay Madria
Affiliations:
School of Computer Engineering, Nanyang Technological University, Singapore, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore, Singapore;School of Computer Engineering, Nanyang Technological University, Singapore, Singapore;Department of Computer Science, University of Missouri, Rolla
Venue:
Data & Knowledge Engineering - Special issue: ER 2003
Year:
2006

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Abstract

Recently, there is an increasing research efforts in XML data mining. These research efforts largely assumed that XML documents are static. However, in reality, the documents are rarely static. In this paper, we propose a novel research problem called XML structural delta mining. The objective of XML structural delta mining is to discover knowledge by analyzing structural evolution pattern (also called structural delta) of history of XML documents. Unlike existing approaches, XML structural delta mining focuses on the dynamic and temporal features of XML data. Furthermore, the data source for this novel mining technique is a sequence of historical versions of an XML document rather than a set of snapshot XML documents. Such mining technique can be useful in many applications such as change detection for very large XML documents, efficient XML indexing, XML search engine, etc. Our aim in this paper is not to provide a specific solution to a particular mining problem. Rather, we present the vision of the mining framework and present the issues and challenges for three types of XML structural delta mining: identifying various interesting structures, discovering association rules from structural deltas, and structural change pattern-based classification.