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Mining N-most interesting itemsets without support threshold by the COFI-tree

Sze Chung Ngan, Tsang Lam, Raymond Chi Wing Wong, Ada Wai Chee Fu
2005 International Journal of Business Intelligence and Data Mining  
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  
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]

Mohammad El-Hajj, Osmar R. Zaïane
2003 Lecture Notes in Computer Science  
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]

Mohammad El-Hajj, Osmar R. Zaïane
2005 Lecture Notes in Computer Science  
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

Aaron Ceglar, John F. Roddick
2006 ACM Computing Surveys  
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

Alisha S.Patel, Mohit Patel
2015 International Journal of Computer Applications  
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

R. Prabamanieswari
2017 International Journal for Research in Applied Science and Engineering Technology  
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

Chun-Wei Lin, Tzung-Pei Hong, Wen-Hsiang Lu
2010 Expert systems with applications  
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

Shakil Ahmed, Frans Coenen, Paul Leng
2006 Knowledge and Information Systems  
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

Osmar R. Zaïane, Mohammad El-Hajj
2005 Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining - KDD '05  
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

A B M R Islam, Tae-Sun Chung
2011 2011 International Conference on Information Science and Applications  
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]

Souad Bouasker
2018 arXiv   pre-print
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

Hong-Jun Jang, Yeongwook Yang, Ji Su Park, Byoungwook Kim
2021 Electronics  
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

Arnaud Soulet, Bruno Crémilleux
2009 Intelligent Data Analysis  
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  
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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