Results 171 to 180 of about 2,506 (215)

On a visual frequent itemset mining

2009 Fourth International Conference on Digital Information Management, 2009
Given a large, dense transaction database, generating interesting frequent patterns in a user friendly manner remains as an important issue in data mining. It is because the minimum support, the most popular statistical significance measurement, is not capable of reflecting the domain user's interest. This paper presents visual frequent itemset mining (
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An Improved Algorithm for Frequent Itemsets Mining

2017 Fifth International Conference on Advanced Cloud and Big Data (CBD), 2017
Based on the classical FP-growth algorithm about frequent itemsets mining, this paper proposes a more efficient non-recursive FPNR-growth algorithm and corresponding data structure. The experimental results show that the FPNR-growth algorithm is superior to the FP-growth algorithm, both in mining time and in storage space.
Hao Jiang, Xu He
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A Decomposition Approach for Mining Frequent Itemsets

Third International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007), 2007
In this paper, instead of proposing the fastest mining algorithm in the world, we present a new approach in mining association rules. We propose a new algorithm - GRA (Gradational Reduction Approach). It adopts three mechanisms to increase the performance of mining.
Jen-Peng Huang, Guo-Cheng Lan, Huang-Cheng Kuo, Tzung-Pei Hong   +3 more
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Efficient mining frequent itemsets algorithms

International Journal of Machine Learning and Cybernetics, 2013
Efficient algorithms for mining frequent itemsets are crucial for mining association rules as well as for many other data mining tasks. It is well known that countTable is one of the most important facility to employ subsets property for compressing the transaction database to new lower representation of occurrences items. One of the biggest problem in
Marghny H. Mohamed, Mohammed M. Darwieesh   +1 more
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Summary queries for frequent itemsets mining

Journal of Systems and Software, 2010
There are many advanced techniques that can efficiently mine frequent itemsets using a minimum-support. However, the question that remains unanswered is whether the minimum-support can really help decision makers to make decisions. In this paper, we study four summary queries for frequent itemsets mining, namely, (1) finding a support-average of ...
Shichao Zhang 0001, Zhi Jin 0001, Jingli Lu   +2 more
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Memory Efficient Frequent Itemset Mining

2018
Frequent itemset mining has been one of the most popular data mining techniques. Despite a large number of algorithms developed to implement this functionality, there is still room for improvement of their efficiency. In this paper, we focus on memory use in frequent itemset mining.
Nima Shahbazi, Rohollah Soltani, Jarek Gryz   +2 more
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On Maximal Frequent Itemsets Mining with Constraints

2018
Recently, a new declarative mining framework based on constraint programming (CP) and propositional satisfiability (SAT) has been designed to deal with several pattern mining tasks. The itemset mining problem has been modeled using constraints whose models correspond to the patterns to be mined.
Saïd Jabbour, Fatima Ezzahra Mana, Imen Ouled Dlala, Badran Raddaoui, Lakhdar Sais   +4 more
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Distributed Frequent Closed Itemsets Mining

2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, 2007
As many large organizations have multiple data sources and the scale of dataset becomes larger and larger, it is inevitable to carry out data mining in the distributed environment. In this paper, we address the problem of mining global frequent closed itemsets in distributed environment.
Chun Liu, Zheng Zheng 0001, Kai-Yuan Cai, Shichao Zhang 0001   +3 more
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An algorithm for mining frequent closed itemsets

2008 3rd International Conference on Intelligent System and Knowledge Engineering, 2008
The problem of mining frequent itemsets plays an essential role in mining association rules, but it is not necessary to mine all frequent itemsets, instead it is sufficient to mine the set of frequent closed itemsets, which is much smaller than the set of all frequent itemsets. In this paper, we present an efficient algorithm, FCI-Miner, for mining all
Tiejun Zhang, Junrui Yang, Xiuqin Wang
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Incremental Frequent Itemsets Mining with MapReduce

2017
Frequent itemsets mining is a common task in data mining. Since sizes of today’s databases go far beyond capabilities of a single machine, recent studies show how to adopt classical algorithms for frequent itemsets mining for parallel frameworks such as MapReduce. Even then, in case of a slight database update a re-run of the MapReduce mining algorithm
Kirill Kandalov, Ehud Gudes
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