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MPSQAR: Mining Quantitative Association Rules Preserving Semantics
2008To avoid the loss of semantic information due to the partition of quantitative values, this paper proposes a novel algorithm, called MPSQAR, to handle the quantitative association rules mining. And the main contributions include: (1) propose a new method to normalize the quantitative values; (2) assign a weight for each attribute to reflect the values ...
Chunqiu Zeng +7 more
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Using Quantitative Association Rules in Collaborative Filtering
2005Recommender systems make information filtering for user by predicting user’s preference to items. Collaborative filtering is the most popular technique in implementing a recommender system. Association rule mining is a powerful data mining method to search for interesting relationships between items by finding the items frequently appeared together in ...
Xiaohua Sun, Fansheng Kong, Hong Chen
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Fuzzy Quantitative Association Rules and Its Applications
2007In recent years, association rules from large databases have received considerable attention and have been applied to various areas such as marketing, retail and finance, et al. While conventional approaches usually deal with databases with binary values, this chapter introduces an approach to discovering association rules from quantitative datasets ...
Peng Yan, Guoqing Chen
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Evaluating Association Rules by Quantitative Pairwise Property Comparisons
2010 IEEE International Conference on Data Mining Workshops, 2010Evaluating association rules is an integral post process in association rule mining. Association rules are examined by measures for their interestingness. Different interestingness measures have been proposed. Given an association rule mining task, measures are assessed and selected against a set of user-specified properties.
Elnaz Delpisheh, John Z. Zhang
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Mining fuzzy similar association rules from quantitative data
2002 Annual Meeting of the North American Fuzzy Information Processing Society Proceedings. NAFIPS-FLINT 2002 (Cat. No. 02TH8622), 2003Data mining of association rules from items in transaction databases has been studied extensively in recent years. In order to discover more practical rules, domain knowledge such as taxonomies of items [9] and similarity among items [11] have been considered to produce generalized association rules and similar association rules respectively.
null Shyue-Liang Wang +2 more
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Optimal Discretization of Quantitative Attributes for Association Rules
2004Association rules for objects with quantitative attributes require the discretization of these attributes to limit the size of the search space. As each such discretization might collapse attribute levels that need to be distinguished for finding association rules, optimal discretization strategies are of interest.
Stefan Born, Lars Schmidt-Thieme
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Revisiting the rules of life for viruses of microorganisms
Nature Reviews Microbiology, 2021Adrienne M S Correa +2 more
exaly