An analytical review of XML association rules mining

被引:50
作者
Moradi, Mohammad [1 ]
Keyvanpour, Mohammad Reza [2 ]
机构
[1] Islamic Azad Univ, Qazvin Branch, Dept Elect Comp & Biomed Engn, Qazvin, Iran
[2] Alzahra Univ, Dept Comp Engn, Tehran, Iran
关键词
XML data mining; Association rules; XML association rules; Categorizing; Challenges; DISCOVERY; FRAMEWORK; PATTERNS;
D O I
10.1007/s10462-012-9376-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Over the past decade, there has been increasing interest in using extensible markup language (XML) which has made it a de facto standard for representing and exchanging data over different systems and platforms (specifically the internet). Due to the popularity of XML and with increasing numbers of XML documents, the process of knowledge discovery from this type of data has found more attention. Although in the last decade several different methods have been proposed for mining XML documents, this research field still is in its infancy compared to traditional data mining. As in relational techniques, in the case of XML documents, association rule mining has a strong research interest. In this paper we have performed a comprehensive study on all of the major works so far done on mining association rules from XML documents. The main contribution of the paper is to provide a reference point for future researches by collecting different techniques and methods concerning the topic; classifying them into a number of categories and creating a complete bibliography of the major published works. We think that this paper can help researchers in XML association rules mining domains to quickly find the current work as the basis for the future activities.
引用
收藏
页码:277 / 300
页数:24
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