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Mining N-most interesting itemsets without support threshold by the COFI-tree
2005
International Journal of Business Intelligence and Data Mining
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In this paper, the problem of mining N-most interesting itemsets is addressed. We make use of the techniques of COFI-tree in order to tackle the problem. ...
Data mining is the discovery of interesting and hidden patterns from a large amount of collected data. ...
Objective: We set our goal to find a fast algorithm to mine N-most interesting k-itemsets without a given minimum support threshold. ...
doi:10.1504/ijbidm.2005.007320
fatcat:mxn4ksjh5zgm7kqcvfldmsbigq
Frame work for association rule mining with updated fp-growth and modified cofi approaches
2016
International Journal of Latest Trends in Engineering and Technology
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Look at the nature of the transaction database of X-COFI-tree or frequent-path-bases of X-COFI-tree. It recommends a list of frequent-path-bases whose support is less than minimum support threshold. ...
In Current Systems, the process of mining of Interesting Association Rules and Frequent Itemsets from a given dataset was done by Apriori based algorithms. ...
doi:10.21172/1.73.502
fatcat:a7crdrnzhbc4lbhrfnyuidndqu
Non-recursive Generation of Frequent K-itemsets from Frequent Pattern Tree Representations
[chapter]
2003
Lecture Notes in Computer Science
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For each frequent item, a relatively small independent tree called COFI-tree, is built summarizing co-occurrences. Finally, a simple and non-recursive mining process mines the COFI-trees. ...
Experimental studies reveal that our approach is efficient and allows the mining of larger datasets than those limited by FP-Tree ...
COFI-tree) for each frequent 1-itemset and mine the trees with simple non-recursive traversals. ...
doi:10.1007/978-3-540-45228-7_37
fatcat:m5u46gaagreobnptkqlb2rmpuy
Finding All Frequent Patterns Starting from the Closure
[chapter]
2005
Lecture Notes in Computer Science
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Although many efficient frequent-pattern mining techniques have been developed in the last decade, most of them assume relatively small databases, leaving extremely large but realistic datasets out of ...
Our implementation shows that our approach outperforms similar state-of-the-art algorithms when mining extremely large datasets by at least one order of magnitude in terms of both execution time and memory ...
F-COFI-tree is created next and it generates all its closed patterns using the same method explained later. Mining a COFI tree starts by finding the frequent-path-bases. ...
doi:10.1007/11527503_10
fatcat:dxz3qb57ajc4rf2c5se7gk7s6a
Association mining
2006
ACM Computing Surveys
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This survey focuses on the fundamental principles of association mining, that is, itemset identification, rule generation, and their generic optimizations. ...
This article presents a survey of association mining fundamentals, detailing the evolution of association mining algorithms from the seminal to the state-of-the-art. ...
Each COFI tree is then mined independently without recursively building further constrained subtrees. ...
doi:10.1145/1132956.1132958
fatcat:37cmcoy7m5gbxadyzxozkcszea
Effective and Innovative Approaches for Comparing Different Multilevel Association Rule Mining for Feature Extraction: A Review
2015
International Journal of Computer Applications
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Because of the multilevel association execution time is reduced and throughput increase in new methods.MRA algorithm using Bayesian probability, concept hierarchy ,COFI-tree method, dynamic concept hierarchy ...
It focuses on the customer relationship management. Apriori algorithm is mainly used for the multilevel association rule mining. ...
COFI-tree method reduces the memory usage in comparison to ML_T2L1 for generating frequent pattern in multilevel. ...
doi:10.5120/19212-1046
fatcat:fy2y6n5mjbgfvoxrigbwwaszmu
NCFP-tree: A Non-Recursive Approach to CFP-tree using Single Conditional Database
2017
International Journal for Research in Applied Science and Engineering Technology
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Different methods introduced by different researchers generated the frequent itemsets by using candidate generation process [1] as well as without candidate generation process [9] within which further ...
Given a transaction database D and a minimum support threshold min-sup, the task of mining frequent pattterns is to find all the frequent patterns in D with respect to min-sup. ...
Hajj and Zarane [8] present the Co-Occurrence Frequent Item tree (or COFI-tree for short) for mining frequent patterns. The presented algorithm is done in two phases. ...
doi:10.22214/ijraset.2017.11058
fatcat:atkqknshejdppelt4jzpcnyfha
Linguistic data mining with fuzzy FP-trees
2010
Expert systems with applications
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The fuzzy FP-tree construction algorithm is thus designed, and the mining process based on the tree is presented. ...
In the past, many algorithms were proposed for mining association rules, most of which were based on items with binary values. ...
Most of the approaches were based on the Apriori algorithm (Agrawal et al., 1993a ), which generated and tested candidate itemsets level by level. ...
doi:10.1016/j.eswa.2009.12.052
fatcat:kv7a7giwwvgn5a7r3pye7rxkiy
Tree-based partitioning of date for association rule mining
2006
Knowledge and Information Systems
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The most computationally d emanding aspect of association rule mining is the identification and counting of support of the frequent sets of items that occur together sufficiently often to be the basis ...
support thresholds. ...
For most real data, the number n of such items is likely to be such that counting the support of all 2 n sets of items (itemsets) is infeasible. ...
doi:10.1007/s10115-006-0010-1
fatcat:osmemt2pnvarxffqumbxnbfmkq
Pattern lattice traversal by selective jumps
2005
Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05
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Regardless of the frequent patterns to discover, either the full frequent patterns or the condensed ones, either closed or maximal, the strategy always includes the traversal of the lattice of candidate ...
We use this approach to efficiently pinpoint maximal patterns at the border of the frequent patterns in the lattice and collect enough information in the process to generate all subsequent patterns. ...
Participation plays a similar role in the mining process as the participation counter in the COFI-tree [4] . ...
doi:10.1145/1081870.1081964
dblp:conf/kdd/ZaianeE05
fatcat:ff3kruf24jg6toqtu4qlfjy2gu
An Improved Frequent Pattern Tree Based Association Rule Mining Technique
2011
2011 International Conference on Information Science and Applications
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This algorithm mines all possible frequent item set without generating the conditional FP tree. ...
It mines the frequent item set without candidate set generation. The main obstacle of FP growth is, it generates a massive number of conditional FP tree. ...
ACKNOWL This research was supported Program through the National (NRF) funded by the Ministr Technology (2010-0013487). ...
doi:10.1109/icisa.2011.5772412
fatcat:qiniwaqpqjevzbizolsaqmw4mq
Characterization and extraction of condensed representation of correlated patterns based on formal concept analysis
[article]
2018
arXiv
pre-print
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We propose to extract a subset without information loss of the sets of frequent correlated and of rare correlated patterns, this subset is called "Condensed Representation". ...
Correlated pattern mining has increasingly become an important task in data mining since these patterns allow conveying knowledge about meaningful and surprising relations among data. ...
For example, BD stands for the itemset composed by the items B and D.
Supports of a Pattern To evaluate an itemset, many interesting measures can be used. ...
arXiv:1810.05570v1
fatcat:utoanqyz3bgarpo6oxb55kbi3q
FP-Growth Algorithm for Discovering Region-Based Association Rule in the IoT Environment
2021
Electronics
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The increased spatial data are being actively utilized in the data mining field. The existing association rule mining algorithms find all items with high correlation in the entire data. ...
Second, frequent pattern growth (FP-Growth) is performed for each transaction divided by region. ...
The best-known constraints are minimum thresholds on support and confidence. Let X, Y be itemsets and r be regions, r: X→Y an association rule, and T a set of transactions of a given database. ...
doi:10.3390/electronics10243091
fatcat:544e3k5ohrbgfcf6obeu33t2va
Mining constraint-based patterns using automatic relaxation
2009
Intelligent Data Analysis
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In practice, current approaches focus on a language and the most generic frameworks mine individually or simultaneously a monotone and an anti-monotone constraints. ...
We study the optimal relaxations. Finally, we provide an experimental illustration of the efficiency of our proposal by experimenting it on several contexts. ...
Acknowledgments This work has been partially supported by the ANR (French Research National Agency) project Bingo2 ANR-07-MDCO-014 which is a follow-up of the first Bingo project (2004)(2005)(2006)(2007 ...
doi:10.3233/ida-2009-0358
fatcat:7lkdv5fxmfhuvjt4wswfj2qr6q
Social Networking Data Research Using Frequent Pattern Mining and Machine Learning Data
2019
International Journal of Engineering and Advanced Technology
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Association rule mining introduces the method to extracts the related data from the datasets using the performance metrics like support and confidence. ...
This problem is addressed by using generic attribute format with frequent pattern mining. ...
COFI (Co-Occurrence Frequent Item set) algorithm also mines the item sets by pruning concept in order to reduce the memory and usage with proper threshold level. ...
doi:10.35940/ijeat.f9352.088619
fatcat:7mfk3kmldzhclkt5a67astv7tm
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