Results 211 to 220 of about 16,254 (263)
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Exception rules in association rule mining
Applied Mathematics and Computation, 2008zbMATH Open Web Interface contents unavailable due to conflicting licenses.
David Tâniar, Wenny Rahayu
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Local mining of Association Rules with Rule Schemas
2009 IEEE Symposium on Computational Intelligence and Data Mining, 2009One of the central problems in Knowledge Discovery in Databases, more precisely in the field of Association Rule Mining, relies on the very large number of rules that classic rule mining systems extract. This problem is usually solved by means of a post-processing step, that filters the entire volume of extracted rules, in order to output only a few ...
Andrei Olaru +2 more
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Association rules mining on MapReduce
Proceedings of the 2nd international Conference on Big Data, Cloud and Applications, 2017Many governments are considering adopting the smart city concept in their cities and implementing big data applications that support smart city components to reach the required level of sustainability and improve the living standards. Smart cities utilize multiple technologies to improve the performance of health, transportation, energy, education, and
Saida El Mendili +2 more
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Proceedings of the tenth international conference on Information and knowledge management, 2001
Association rule mining is a well-researched area where many algorithms have been proposed to improve the speed of mining. In this paper, we propose an innovative algorithm called Rapid Association Rule Mining (RARM) to once again break this speed barrier. It uses a versatile tree structure known as the Support-Ordered Trie Itemset (SOTrieIT) structure
Amitabha Das +2 more
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Association rule mining is a well-researched area where many algorithms have been proposed to improve the speed of mining. In this paper, we propose an innovative algorithm called Rapid Association Rule Mining (RARM) to once again break this speed barrier. It uses a versatile tree structure known as the Support-Ordered Trie Itemset (SOTrieIT) structure
Amitabha Das +2 more
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Parallel mining of association rules
IEEE Transactions on Knowledge and Data Engineering, 1996We consider the problem of mining association rules on a shared nothing multiprocessor. We present three algorithms that explore a spectrum of trade-offs between computation, communication, memory usage, synchronization, and the use of problem specific information.
Rakesh Agrawal 0001, John C. Shafer
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Mining fuzzy association rules
Proceedings of the sixth international conference on Information and knowledge management, 1997In his paper, we introduce a novel technique, called F-APACS, for mining jkzy association rules. &istlng algorithms involve discretizing the domains of quantitative attrilmtes into intervals so as to discover quantitative association rules. i%ese intervals may not be concise and meaning@ enough for human experts to easily obtain nontrivial knowledge ...
Keith C. C. Chan, Wai-Ho Au
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Mining negative association rules
Proceedings ISCC 2002 Seventh International Symposium on Computers and Communications, 2003The focus of this paper is the discovery of negative association rules. Such association rules are complementary to the sorts of association rules most often encountered in the literature and have the forms of X/spl rarr/ -Y or -X/spl rarr/Y. We present a rule discovery algorithm that finds a useful subset of valid negative rules.
Xiaohui Yuan 0001 +3 more
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Mining Utility Association Rules
Proceedings of the 2018 10th International Conference on Computer and Automation Engineering, 2018Mining high utility itemset is to find the itemsets that can bring higher profits to the company, which considers both of the profits and purchased quantities for the items. However, from the high utility itemsets, we cannot know what products should be recommended to the customer such that the profit can be increased when he/she bought some products ...
Yue-Shi Lee, Show-Jane Yen
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Mining Causal Association Rules
2013 IEEE 13th International Conference on Data Mining Workshops, 2013Discovering causal relationships is the ultimate goal of many scientific explorations. Causal relationships can be identified with controlled experiments, but such experiments are often very expensive and sometimes impossible to conduct. On the other hand, the collection of observational data has increased dramatically in recent decades.
Jiuyong Li +5 more
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On reconfigurable association rule mining
2012 IEEE International Conference on Granular Computing, 2012As one of the most important techniques for knowledge discovery, association rule mining is known to be very computational intensive. Many hardware architectures were proposed to speed up association rule mining. Generally, theses methods are based on the usage of systolic arrays with preserved hardware resources.
Wen-Tsai Liao, Ming-Syan Chen
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