Efficient streaming data association rule mining
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In this paper, we propose a framework, called XAR-Miner, for mining ARs from XML documents efficiently and effectively. In XAR-Miner, raw XML data are first transformed to either an Indexed Content Tree (IX-tree) or Multi-relational databases (Multi-DB), depending on the size of
Document clustering is one of the important research issues in the field of text mining, where the documents are grouped without predefined categories or labels. High dimensionality is a major challenge in document clustering. Some of the recent algorithms address this problem by
Department of Computer Science & Engineering/Shriram College of Engineering & Management [SRCEM] Banmore, Gwalior (MP)/India, 474003 _______________________________________________________________________________________ Abstract: Data mining is sorting through data to identify p
Association rule mainly focuses on large transactional databases. In association rule mining all items are considered with equal weightage. But it is not suitable for all datasets. The weight should be considered based on the importance of the item. In our previous work HITS algo
A great research work has been done in last decade in association rules mining (ARM) algorithms . Therefore, various algorithms were proposed to discover frequent item sets and then mine association rules. Apriori algorithm is the most frequently used algorithm for generating ass
In this paper we propose to use association rules to mine the association relationships among different genes under the same experimental conditions. These kinds of relations may also exist across many different experiments with various experimental conditions. In this paper, a n