Results 211 to 220 of about 60,734 (264)

A Statistical Theory for Quantitative Association Rules

Journal of Intelligent Information Systems, 1999
Association rules are a key data-mining tool and as such have been well researched. So far, this research has focused predominantly on databases containing categorical data only. However, many real-world databases contain quantitative attributes and current solutions for this case are so far inadequate.
Yonatan Aumann, Yehuda Lindell
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Quantitative Association Rules Based on Distance

2009 International Conference on Computational Intelligence and Software Engineering, 2009
In association analysis, mining the continuous attributes may reveal useful and interesting insights about the data objects which are of continuous attributes. Quantitative association rules are aimed to deal with the relationships among continuous attributes of data objects.
Hai-Dong Meng, Yu-Chen Song, Hai-Tao Shen   +2 more
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Discovering and managing quantitative association rules

Proceedings of the 22nd ACM international conference on Information & Knowledge Management, 2013
Although association rule mining has been studied in the literature for quite a while and numerical attributes are prevalent, perhaps surprisingly, the state-of-the-art quantitative association rule mining is rather inefficient and ineffective in discovering all useful rules.
Chunyao Song, Tingjian Ge
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Quantitative association rules over incomplete data

SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218), 2002
This paper explores the use of principle component analysis (PCA) to estimate missing values during the mining of quantitative association rules. An example of such association may be "15% of customers spend $100-$300 every month will have two cable outlets at home".
V. Ng, J. Lee
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Density-Based Mining of Quantitative Association Rules

2000
Many algorithms have been proposed for mining of boolean association rules. However, very little work has been done in mining quantitative association rules. Although we can transform quantitative attributes into boolean attributes, this approach is not effective and is difficult to scale up for high dimensional case and also may result in many ...
Yiu, SM, Wang, L, Cheung, DWL, Zhou, B
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Mining fuzzy quantitative association rules

Proceedings 11th International Conference on Tools with Artificial Intelligence, 2003
Given a relational database and a set of fuzzy terms defined for some attributes we consider the problem of mining fuzzy quantitative association rules that may contain crisp values, intervals, and fuzzy terms in both antecedent and consequent. We present an algorithm extended from the equi-depth partition (EDP) algorithm for solving this problem.
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Trends in quantitative association rule mining techniques

2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS), 2015
Association rule mining (ARM) techniques are effective in extracting frequent patterns and hidden associations among data items in various databases. These techniques are widely used for learning behavior, predicting events and making decisions at various levels.
Dhrubajit Adhikary, Swarup Roy
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Preserving Privacy in Mining Quantitative Associations Rules

International Journal of Information Security and Privacy, 2009
Association rule mining is an important data mining method that has been studied extensively by the academic community and has been applied in practice. In the context of association rule mining, the state-of-the-art in privacy preserving data mining provides solutions for categorical and Boolean association rules but not for quantitative association ...
Madhu V. Ahluwalia, Aryya Gangopadhyay, Zhiyuan Chen   +2 more
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Mining Fuzzy Association Rules in Quantitative Databases

Applied Mechanics and Materials, 2012
In this paper, we introduce a novel technique for mining fuzzy association rules in quantitative databases. Unlike other data mining techniques who can only discover association rules in discrete values, the algorithm reveals the relationships among different quantitative values by traversing through the partition grids and produces the corresponding ...
Yi Ming Bai, Xian Yao Meng, Xin Jie Han
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Mining High Utility Quantitative Association Rules

2007
Mining weighted association rules considers the profits of items in a transaction database, such that the association rules about important items can be discovered. However, high profit items may not always be high revenue products, since purchased quantities of items would also influence the revenue for the items. This paper considers both profits and
Show-Jane Yen, Yue-Shi Lee
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