Abstract
Mining of association rules is to find associations among data items that appear together in some transactions or business activities. As of today, algorithms for association rule mining, as well as for other data mining tasks, are mostly applied to relational databases. As XML being adopted as the universal format for data storage and exchange, mining associations from XML data becomes an area of attention for researchers and developers. The challenge is that the semi-structured data format in XML is not directly suitable for traditional data mining algorithms and tools. In this paper we present an intelligent encoding method to encode XML tree-nodes. This method is used to store the XML data in 2-dimensional tables that can be easily accessed via indexing using knowledge. The hierarchical relationship in the original XML tree structure is embedded in the encoding. We applied this method in some applications, such as mining of association rules.
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Kim, HK. (2006). Intelligent Frameworks for Encoding XML Elements Using Mining Algorithm. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_96
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DOI: https://doi.org/10.1007/11893004_96
Publisher Name: Springer, Berlin, Heidelberg
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