Approximate weighted frequent pattern mining with/without noisy environments
Knowledge-Based Systems
An efficient mining algorithm for maximal weighted frequent patterns in transactional databases
Knowledge-Based Systems
Efficient mining of maximal correlated weight frequent patterns
Intelligent Data Analysis
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XML data are being a standard in many areas such as internet and public documentation. Therefore, there are many kinds of documentation or web sites which are using XML expressions. To extract some useful data among multiple XML data, we need to research data mining algorithm to XML data. And many kinds of techniques have been researched to speed up the query performance about XML data. In this paper, we analyze the XML query pattern and propose the data mining technique which extracts the similar XML query pattern. The proposed method based on Weighted- FP-growth algorithm is applied to XML query subtrees. And we experimented our technique compared with FP-growth algorithm and Apriori algorithm. The proposed method outperforms any other methods in query result of the repeatedly occurring queries.