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Efficient algorithms for the mining of constrained frequent patterns from uncertain data
2010
SIGKDD Explorations
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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
2005
Knowledge and Information Systems
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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
2013
Knowledge-Based Systems
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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
Fourth IEEE International Conference on Data Mining (ICDM'04)
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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]
2019
Studies in Computational Intelligence
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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]
2003
Lecture Notes in Computer Science
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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
2014
International Journal of Computer Applications
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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]
2009
Proceedings of the 2009 SIAM International Conference on Data Mining
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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
2002
Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02
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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
2002
Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02
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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]
2004
Proceedings of the 2004 SIAM International Conference on Data Mining
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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
2013
International Journal of Computer Applications
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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
2008
Data mining and knowledge discovery
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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
2007
Data mining and knowledge discovery
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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]
2009
Lecture Notes in Computer Science
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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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