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Generating Closed Frequent Itemsets with the Frequent Pattern List
2010 2nd International Workshop on Database Technology and Applications, 2010An approach is proposed to discover closed frequent itemsets with a simple linear list structure called the Frequent Pattern List(FPL) in transaction database. The approach selects representation patterns from candidate itemsets to reduce combinational space of frequent patterns.
Qin Li, Sheng Chang
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Mining Maximal Frequent Itemsets with Frequent Pattern List
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007Mining frequent itemsets is a major aspect of association rule research. However, the mining of the complete of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of maximal frequent itemsets.
Jin Qian, Feiyue Ye
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Mining Supplemental Frequent Patterns
2008The process of resource distribution and load balance of a distributed P2P network can be described as the process of mining Supplement Frequent Patterns (SFPs) from query transaction database. With given minimum support (min_sup) and minimum share support (min_share_sup), each SFP includes a core frequent pattern (BFP) used to draw other frequent or ...
Yintian Liu +4 more
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Balancing the Analysis of Frequent Patterns
2014A main challenge in pattern mining is to focus the discovery on high-quality patterns. One popular solution is to compute a numerical score on how well each discovered pattern describes the data. The best rating patterns are then the most analyzed by the data expert.
Arnaud Giacometti +2 more
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Mining image frequent patterns based on a frequent pattern list in image databases
The Journal of Supercomputing, 2019The goal of image mining is to find the useful information hidden in image databases. The 9DSPA-Miner approach uses the Apriori strategy to mine the image database, where each image is represented by the 9D-SPA representation. It presents a reasoning method to reason the unknown spatial relation that satisfies the spatial consistency.
Ye-In Chang +4 more
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An Efficient Approach for Mining Frequent Patterns Based on Traversing a Frequent Pattern Tree
2008 International Conference on Computer Science and Software Engineering, 2008Mining frequent patterns is an important task for knowledge discovery, which discovers the groups of items appearing always together excess of a user specified threshold. A famous algorithm for mining frequent patterns is FP-Growth which constructs a structure called FP-tree and recursively mines frequent patterns from this structure by building ...
Show-Jane Yen +3 more
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On Closed Constrained Frequent Pattern Mining
Fourth IEEE International Conference on Data Mining (ICDM'04), 2005Constrained frequent patterns and closed frequent patterns are two paradigms aimed at reducing the set of extracted patterns to a smaller, more interesting, subset. Although a lot of work has been done with both these paradigms, there is still confusion around the mining problem obtained by joining closed and constrained frequent patterns in a unique ...
Bonchi F, Lucchese C
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Constrained frequent pattern mining
ACM SIGKDD Explorations Newsletter, 2002It has been well recognized that frequent pattern mining plays an essential role in many important data mining tasks. However, frequent pattern mining often generates a very large number of patterns and rules, which reduces not only the efficiency but also the effectiveness of mining.
Jian Pei 0001, Jiawei Han 0001
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On computing condensed frequent pattern bases
2002 IEEE International Conference on Data Mining, 2002. Proceedings., 2003Frequent pattern mining has been studied extensively. However, the effectiveness and efficiency of this mining is often limited, since the number of frequent patterns generated is often too large. In many applications it is sufficient to generate and examine only frequent patterns with support frequency in close-enough approximation instead of in full ...
Pei, Jian +3 more
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MRFP: Discovery Frequent Patterns Using MapReduce Frequent Pattern Growth
2016 International Conference on Network and Information Systems for Computers (ICNISC), 2016In this paper, a novelty of a new method has been presented. MRFP-Growth is implementing to solve the problem of discovering frequent patterns with massive datasets. Most of the frequent patterns algorithms are unable to manipulate with the large datasets, our scheme implement FP-Growth method under MapReduce framework in Hadoop platform to decrease ...
Arkan A. G. Al-Hamodi, Songfeng Lu
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