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Efficient algorithms for the mining of constrained frequent patterns from uncertain data

Carson Kai-Sang Leung, Dale A. Brajczuk
2010 SIGKDD Explorations  
This calls for constrained mining, which aims to find only those frequent patterns that are interesting to the user. Moreover, there are also many  ...  Mining of frequent patterns is one of the popular knowledge discovery and data mining (KDD) tasks.  ...  However, like its counterpart for mining frequent patterns from precise data (i.e., FP-growth), the UF-growth algorithm for mining frequent patterns from uncertain data also suffers from the following  ... 
doi:10.1145/1809400.1809425 fatcat:snwi42cepbdebe5xdk7halt3wi

On condensed representations of constrained frequent patterns

Francesco Bonchi, Claudio Lucchese
2005 Knowledge and Information Systems  
Constrained 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 framework.  ...  Conclusions In this paper we have addressed the problem of mining frequent constrained closed patterns from a qualitative point of view.  ... 
doi:10.1007/s10115-005-0201-1 fatcat:k3criizmxfga5kehzltbkcs75e

Interrelation analysis of celestial spectra data using constrained frequent pattern trees

Jifu Zhang, Xujun Zhao, Sulan Zhang, Shu Yin, Xiao Qin
2013 Knowledge-Based Systems  
Next, we propose a concept of constrained frequent pattern trees (CFP) along with an algorithm used to construct CFPs, aiming to improve the efficiency and pertinence of association rule mining.  ...  Association rule mining, in which generating frequent patterns is a key step, is an effective way of identifying inherent and unknown interrelationships between characteristics of celestial spectra data  ...  a constrained frequent pattern tree or CFP tree for short.  ... 
doi:10.1016/j.knosys.2012.12.013 fatcat:uetlaxjtibbmbadjpws6d2tzra

On Closed Constrained Frequent Pattern Mining

F. Bonchi, C. Lucchese
Fourth IEEE International Conference on Data Mining (ICDM'04)  
Constrained 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 framework.  ...  Conclusions In this paper we have addressed the problem of mining frequent constrained closed patterns from a qualitative point of view.  ... 
doi:10.1109/icdm.2004.10093 dblp:conf/icdm/BonchiL04 fatcat:qbh5ja4febbfhm7owbd7ssgiau

Discriminant Chronicle Mining [chapter]

Yann Dauxais, David Gross-Amblard, Thomas Guyet, André Happe
2019 Studies in Computational Intelligence  
Merci à tous !  ...  Merci à tous les employés de l'IRISA d'en faire un lieu de travail convivial, et plus particulièrement, merci à tous les membres de l'équipe Lacodam, tous très sympathiques et prêts à se sacrifier pour  ...  The purpose of SPIRIT is to mine sequential patterns constrained by regular expressions.  ... 
doi:10.1007/978-3-030-18129-1_5 fatcat:m4uac72qq5e3vn5qvtfgi537ru

Efficient Mining of Indirect Associations Using HI-Mine [chapter]

Qian Wan, Aijun An
2003 Lecture Notes in Computer Science  
While most of the existing algorithms are developed for efficient mining of frequent patterns, it has been noted recently that some of the infrequent patterns, such as indirect associations, provide useful  ...  In this paper, we propose an efficient algorithm, called HI-mine, based on a new data structure, called HI-struct, for mining the complete set of indirect associations between items.  ...  Acknowledgments This research is partially supported by a research grant from the Natural Sciences and Engineering Research Council (NSERC) of Canada. We would like to thank Mr.  ... 
doi:10.1007/3-540-44886-1_17 fatcat:rp7vp272xjh3bj2v6cb5ugzoqa

Survey on Constrained based Data Stream Mining

Lini SusanKurien, Sreekumar K, Minu KK
2014 International Journal of Computer Applications  
In order to obtain that, some constraint based mining techniques, which acts as a filter to the large result set retrieved from traditional pattern mining techniques.  ...  There are certain techniques to deal with data streams, in particular, finding the frequent or sequential patterns that occur repeatedly.  ...  Constraint frequent pattern mining with a patter growth view finds all frequent itemset that satisfy the constraint and then the pattern growth mining method generates and test only a few among them.  ... 
doi:10.5120/18834-0348 fatcat:7pkf7x2o2nhpfl5g5beap6p4ee

Grammar Mining [chapter]

Siegfried Nijssen, Luc De Raedt
2009 Proceedings of the 2009 SIAM International Conference on Data Mining  
We introduce the problem of grammar mining, where patterns are context-free grammars, as a generalization of a large number of common pattern mining tasks, such as tree, sequence and itemset mining.  ...  The proposed system offers data miners the possibility to specify and explore pattern domains declaratively, in a way which is very similar to the declarative specification of regular expressions in popular  ...  frequent within a fixed domain of patterns.  ... 
doi:10.1137/1.9781611972795.88 dblp:conf/sdm/NijssenR09 fatcat:enp53rt6ozdn3a6c5xqr2jjkmu

Mining sequential patterns with constraints in large databases

Jian Pei, Jiawei Han, Wei Wang
2002 Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02  
An extended framework is developed based on a sequential pattern growth methodology.  ...  In this paper, we investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit our missions well.  ...  The work was supported in part by research grants from NSERC and NCE of Canada, and the University of Illinois, and a gift from Microsoft Research. We thank Dr. Mohammed J.  ... 
doi:10.1145/584792.584799 dblp:conf/cikm/PeiHW02 fatcat:xmkgn4jc25ap7aarmfkoqiwoie

Mining sequential patterns with constraints in large databases

Jian Pei, Jiawei Han, Wei Wang
2002 Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02  
An extended framework is developed based on a sequential pattern growth methodology.  ...  In this paper, we investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit our missions well.  ...  The work was supported in part by research grants from NSERC and NCE of Canada, and the University of Illinois, and a gift from Microsoft Research. We thank Dr. Mohammed J.  ... 
doi:10.1145/584796.584799 fatcat:to5ls552fvfopnlptkm5u7b6na

Mining Relationships Between Interacting Episodes [chapter]

Carl H. Mooney, John F. Roddick
2004 Proceedings of the 2004 SIAM International Conference on Data Mining  
The detection of recurrent episodes in long strings of tokens has attracted some interest and a variety of useful methods have been developed.  ...  This paper discusses an approach for finding such relationships through the proposal of a robust and efficient search strategy and effective user interface both of which are validated through experiment  ...  The results of the mining run (frequent episodes) and the discovered frequent interactions are then able to be viewed in both text format and as a directed graph.  ... 
doi:10.1137/1.9781611972740.1 dblp:conf/sdm/MooneyR04 fatcat:6lk6n7vdmjezdouyz3i4z3dgli

Survey on Sequential Pattern Mining Algorithms

V. ChandraShekharRao, P. Sammulal
2013 International Journal of Computer Applications  
Sequential pattern mining is a significant data-mining method for determining time-related behavior in sequence databases.  ...  The information achieved from sequential pattern mining can be used in marketing, medical records, sales analysis, and so on.  ...  WAP-MINE: It is a pattern growth and tree structure-mining technique with its WAP-tree structure.  ... 
doi:10.5120/13301-0782 fatcat:eee6r7dtbffmfphbb4y4shh3be

An integrated, generic approach to pattern mining: data mining template library

Vineet Chaoji, Mohammad Al Hasan, Saeed Salem, Mohammed J. Zaki
2008 Data mining and knowledge discovery  
Frequent pattern mining (FPM) is an important data mining paradigm to extract informative patterns like itemsets, sequences, trees, and graphs.  ...  It uses a novel pattern property hierarchy to define and mine different pattern types.  ...  generic frequent pattern mining algorithm.  ... 
doi:10.1007/s10618-008-0098-x fatcat:7ffj62b7zjgnzgrl3jzjb5655a

Frequent pattern mining: current status and future directions

Jiawei Han, Hong Cheng, Dong Xin, Xifeng Yan
2007 Data mining and knowledge discovery  
Frequent pattern mining has been a focused theme in data mining research for over a decade.  ...  In this article, we provide a brief overview of the current status of frequent pattern mining and discuss a few promising research directions.  ...  The pattern-growth mining algorithm extends a frequent graph by adding a new edge, in every possible position.  ... 
doi:10.1007/s10618-006-0059-1 fatcat:fpblaafhurfbtiimurret4idde

Mining Graph Evolution Rules [chapter]

Michele Berlingerio, Francesco Bonchi, Björn Bringmann, Aristides Gionis
2009 Lecture Notes in Computer Science  
Then, similar to the classical association rules framework, we derive graph-evolution rules from frequent patterns that satisfy a given minimum confidence constraint.  ...  In this paper we introduce graph-evolution rules, a novel type of frequency-based pattern that describe the evolution of large networks over time, at a local level.  ...  Then conventional graph-mining techniques are applied to mine frequent patterns. However, there are several differences to our approach.  ... 
doi:10.1007/978-3-642-04180-8_25 fatcat:vtv7guizvzanrg5az2fdelq2kq
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