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.

Keywords: Versions of XML documents; Structural delta; Dynamic metrics; XML structural delta mining; Research issues; Applications

Article Outline

1. Introduction

1.1. Motivation

1.2. The framework

1.3. Paper organization

2. Related work

2.1. XML change detection

2.2. XML data mining

3. Preliminaries

3.1. Types of XML structural changes

3.2. XML structural delta

3.3. Dynamic metrics

3.4. XML structural delta mining

4. Discovering interesting structures

4.1. Frequently changing structure

4.2. Frozen structure

4.3. Periodic dynamic structure

4.4. Increasing and decreasing dynamic structures

4.5. Outlier structure

5. Discovering association rules

5.1. Positive association rule mining

5.2. Negative association rule mining

5.3. Specialized association rule mining

6. Structure change pattern-based classification

7. Research issues

7.1. Duration of real data collection

7.2. Determining schedules for structural delta generation

7.3. Efficient and scalable structural change detection

7.4. Scalable and efficient mining algorithms

7.5. Semantic-conscious algorithms

7.6. Unified mining framework

8. Applications

8.1. Applications of interesting structures

8.1.1. Efficient change detection for very large XML documents

8.1.2. Efficient XML indexing

8.1.3. Dynamic-conscious XML caching

8.1.4. Semantic meaning extraction

8.2. Applications of XML structural delta association

8.2.1. Structure-based document clustering

8.2.2. Semantic XML search engine

8.3. Applications of change pattern-based classification

9. Conclusions

References

Vitae