Frequent Pattern Discovery and Association Rule Mining of XML Data

Frequent Pattern Discovery and Association Rule Mining of XML Data

Author: 
Ding, Qin
Place: 
Hershey, PA
Publisher: 
IGI Global
Date published: 
2011
Record type: 
Responsibility: 
Sundarraj, Gnanasekaran, jt. author
Editor: 
Tagarelli, Andrea
Source: 
XML Data Mining
Subject: 
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.

Series: 
Advances in Data Mining and Database Management

CITATION: Ding, Qin. Frequent Pattern Discovery and Association Rule Mining of XML Data edited by Tagarelli, Andrea . Hershey, PA : IGI Global , 2011. XML Data Mining - Available at: https://library.au.int/frfrequent-pattern-discovery-and-association-rule-mining-xml-data