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Classification Based upon Frequent Patterns
2001In this paper a new classification algorithm based upon frequent patterns is proposed. A frequent pattern is a generalization of the concept of a frequent item set, used in association rule mining. First of all, the collection of frequent patterns in the training set is constructed.
Pijls, Wim, Potharst, Rob
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Summarizing probabilistic frequent patterns
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013Mining probabilistic frequent patterns from uncertain data has received a great deal of attention in recent years due to the wide applications. However, probabilistic frequent pattern mining suffers from the problem that an exponential number of result patterns are generated, which seriously hinders further evaluation and analysis.
Chunyang Liu, Ling Chen, Chengqi Zhang
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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, Jiawei Han
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The Studies of Mining Frequent Patterns Based on Frequent Pattern Tree
2009Mining frequent patterns is to discover the groups of items appearing always together excess of a user specified threshold. Many approaches have been proposed for mining frequent pattern. However, either the search space or memory space is huge, such that the performance for the previous approach degrades when the database is massive or the threshold ...
Show-Jane Yen +4 more
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Discovering frequent pattern pairs
Intelligent Data Analysis, 2013Cubes and association rules discover frequent patterns in a data set, most of which are not significant. Thus previous research has introduced search constraints and statistical metrics to discover significant patterns and reduce processing time. We introduce cube pairs (comparing cube groups based on a parametric statistical test) and rule pairs ...
Ordonez, Carlos, Chen, Zhibo
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Maintenance of Frequent Patterns
2009This chapter surveys the maintenance of frequent patterns in transaction datasets. It is written to be accessible to researchers familiar with the field of frequent pattern mining. The frequent pattern maintenance problem is summarized with a study on how the space of frequent patterns evolves in response to data updates.
Feng, Mengling +3 more
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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 Frequent Ordered Patterns
2005Mining frequent patterns has been studied popularly in data mining research. All of previous studies assume that items in a pattern are unordered. However, the order existing between items must be considered in some applications. In this paper, we first give the formal model of ordered patterns and discuss the problem of mining frequent ordered ...
Zhi-Hong Deng +3 more
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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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Uncertain Frequent Pattern Mining
2014Frequent pattern mining aims to discover implicit, previously unknown and potentially useful knowledge—in the form of frequently occurring sets of items—that are embedded in data. Many of the models and algorithms developed in the early days mine frequent patterns from traditional transaction databases of precise data such as shopper market basket data,
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