Frequent Pattern Discovery and Association Rule Mining of XML Data-Reference-Cited by-同舟云学术

Frequent Pattern Discovery and Association Rule Mining of XML Data

Published:2013 Issue: Volume: Page:859-879
ISSN:
Container-title:Data Mining
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Author:

Ding Qin¹,Sundarraj Gnanasekaran²

Affiliation:

1. East Carolina University, USA

2. Pennsylvania State University, USA

Abstract

Finding frequent patterns and association rules in large data has become a very important task in data mining. Various algorithms have been proposed to solve such problems, but most algorithms are only applicable to relational data. With the increasing use and popularity of XML representation, it is of importance yet challenging to find solutions to frequent pattern discovery and association rule mining of XML data. The challenge comes from the complexity of the structure in XML data. In this chapter, we provide an overview of the state-of-the-art research in content-based and structure-based mining of frequent patterns and association rules from XML data. We also discuss the challenges and issues, and provide our insight for solutions and future research directions.

Publisher

IGI Global

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