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Frequent Pattern Discovery and Association Rule Mining of XML Data

Frequent Pattern Discovery and Association Rule Mining of XML Data

Qin Ding, Gnanasekaran Sundarraj
Copyright: © 2012 |Pages: 21
ISBN13: 9781613503560|ISBN10: 1613503563|EISBN13: 9781613503577
DOI: 10.4018/978-1-61350-356-0.ch011
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MLA

Ding, Qin, and Gnanasekaran Sundarraj. "Frequent Pattern Discovery and Association Rule Mining of XML Data." XML Data Mining: Models, Methods, and Applications, edited by Andrea Tagarelli, IGI Global, 2012, pp. 243-263. https://doi.org/10.4018/978-1-61350-356-0.ch011

APA

Ding, Q. & Sundarraj, G. (2012). Frequent Pattern Discovery and Association Rule Mining of XML Data. In A. Tagarelli (Ed.), XML Data Mining: Models, Methods, and Applications (pp. 243-263). IGI Global. https://doi.org/10.4018/978-1-61350-356-0.ch011

Chicago

Ding, Qin, and Gnanasekaran Sundarraj. "Frequent Pattern Discovery and Association Rule Mining of XML Data." In XML Data Mining: Models, Methods, and Applications, edited by Andrea Tagarelli, 243-263. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-356-0.ch011

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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.

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