Abstract
The itemset tree data structure is used in targeted association mining to find rules within a user’s sphere of interest. In this paper, we propose two enhancements to the original unordered itemset trees. The first enhancement consists of sorting all nodes in lexical order based upon the itemsets they contain. In the second enhancement, called the Min-Max Itemset Tree, each node was augmented with minimum and maximum values that represent the range of itemsets contained in the children below. For demonstration purposes, we provide a comprehensive evaluation of the effects of the enhancements on the itemset tree querying process by performing experiments on sparse, dense, and categorical datasets.
This project was funded in part by the Louisiana Highway Safety Commission.
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Lavergne, J., Benton, R., Raghavan, V.V. (2012). Min-Max Itemset Trees for Dense and Categorical Datasets. In: Chen, L., Felfernig, A., Liu, J., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2012. Lecture Notes in Computer Science(), vol 7661. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34624-8_6
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DOI: https://doi.org/10.1007/978-3-642-34624-8_6
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