Mining Association Rules from XML DocumentsLaura Irina Rusu (La Trobe University, Australia), Wenny Rahayu (La Trobe University, Australia) and David Taniar (Monash University, Australia)
Copyright © 2007.
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DOI: 10.4018/978-1-59904-228-2.ch004
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MLA
Rusu, Laura Irina, Wenny Rahayu and David Taniar. "Mining Association Rules from XML Documents." Web Data Management Practices: Emerging Techniques and Technologies. IGI Global, 2007. 79-103. Web. 19 Jun. 2013. doi:10.4018/978-1-59904-228-2.ch004
APA
Rusu, L. I., Rahayu, W., & Taniar, D. (2007). Mining Association Rules from XML Documents. In A. Vakali, & G. Pallis (Eds.), Web Data Management Practices: Emerging Techniques and Technologies (pp. 79-103). Hershey, PA: Idea Group Publishing. doi:10.4018/978-1-59904-228-2.ch004
Chicago
Rusu, Laura Irina, Wenny Rahayu and David Taniar. "Mining Association Rules from XML Documents." In Web Data Management Practices: Emerging Techniques and Technologies, ed. Athena Vakali and George Pallis, 79-103 (2007), accessed June 19, 2013. doi:10.4018/978-1-59904-228-2.ch004
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  | | TopAbstractThis chapter presents some of the existing mining techniques for extracting association rules out of XML documents, in the context of rapid changes in the Web knowledge discovery area. The initiative of this study was driven by the fast emergence of XML (eXtensible Markup Language) as a standard language for representing semi-structured data and as a new standard of exchanging information between different applications. The data exchanged as XML documents becomes every day richer and richer, so the necessity to not only store these large volume of XML data for later use, but to mine them as well, to discover interesting information, has became obvious. The hidden knowledge can be used in various ways, for example to decide on a business issue or to make predictions about future e-customer behaviour in a web-application. One type of knowledge which can be discovered in a collection of XML documents relates to association rules between parts of the document, and this chapter presents some of the top techniques for extracting them. TopComplete Chapter List
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