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Efficient Vertical Mining of Frequent Closures and Generators [chapter]

Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin
2009 Lecture Notes in Computer Science  
The effective construction of many association rule bases requires the computation of both frequent closed and frequent generator itemsets (FCIs/FGs).  ...  Experimental results indicate that Touch is highly efficient and outperforms its levelwise competitors.  ...  Section 2 lists the basic concepts of frequent itemset mining and presents the vertical depth-first mining strategy of Charm. In Section 3, we introduce a new FG-miner algorithm called Talky-G.  ... 
doi:10.1007/978-3-642-03915-7_34 fatcat:nr5esej7tjb7noia6lel35ewaq

A Novel Algorithm for Mining Closed Sequential Patterns

Purushothama Raju V, Saradhi Varma G.P
2015 International Journal of Data Mining & Knowledge Management Process  
The results show that the proposed algorithm NCSP can find closed sequential patterns efficiently and outperforms CloSpan by an order of magnitude.  ...  To the best of our knowledge, our algorithm is the first algorithm that utilizes vertical bitmap representation for closed sequential pattern mining.  ...  Close first employs bottom-up search to find out the generators and then calculates the closure of all the generators. FPclose [10] mines closed itemsets and it is based on FP-growth method.  ... 
doi:10.5121/ijdkp.2015.5104 fatcat:3yclmhve2jgnfijctfelq7jv6q

An Efficient Algorithm for Mining Maximal Frequent Item Sets

A.M.J. Md. Zubair Rahman, P. Balasubram
2008 Journal of Computer Science  
Problem Statement: In today's life, the mining of frequent patterns is a basic problem in data mining applications.  ...  It removes all the non-maximal frequent item-sets to get exact set of MFI directly. It worked efficiently when the number of item-sets and tid-sets is more.  ...  The vertical representation allows simple and efficient support counting Basic Properties of Itemset-Tidset Pairs We use the concept of a closure operation [24, 25] to check if a given itemset X is closed  ... 
doi:10.3844/jcssp.2008.638.645 fatcat:grbm65bnknelxc2thgpdcxtpmm

Mining Closed Sequential Patterns in Large Sequence Databases

Purushothama Raju V, Saradhi Varma G.P
2015 International Journal of Database Management Systems  
Closed sequential pattern mining is an important technique among the different types of sequential pattern mining, since it preserves the details of the full pattern set and it is more compact than sequential  ...  In this paper, we propose an efficient algorithm CSpan for mining closed sequential patterns.  ...  It first finds level-wise frequent itemsets using Apriori strategy, and mines all minimal generators. In the second step, it computes the closure of all minimal generators.  ... 
doi:10.5121/ijdms.2015.7103 fatcat:dpadzgyhb5em7ghgcieunhhv6m

Fast and memory efficient mining of frequent closed itemsets

C. Lucchese, S. Orlando, R. Perego
2006 IEEE Transactions on Knowledge and Data Engineering  
This paper presents a new scalable algorithm for discovering closed frequent itemsets, which are a lossless, condensed representation of all the frequent itemsets and associated supports that can be mined  ...  Our algorithm exploits a depth-first visit of the search space, and a bitwise vertical representation of the database.  ...  DCI Closed inherits from DCI [8, 7] -an efficient algorithm to mine frequent itemsets previously proposed -the in-core vertical bitwise representation of the dataset, and several optimization heuristics  ... 
doi:10.1109/tkde.2006.10 fatcat:fc2u5at2unfb5fe7vciwj3p3pm

A Systematic Literature Review of Frequent Pattern Mining Techniques

Rajendra Chouhan, Er. Khushboo Sawant, Dr. Harish Patidar
2018 International Journal of Trend in Scientific Research and Development  
So still there is a need to update and enhance the existing frequent pattern mining techniques so that we can get the more efficient methods for the same task.  ...  In this paper, a study of all the modern and most popular frequent pattern mining technique is also performed.  ...  Frequent pattern mining is used to prune the search space and limit the number of association rules being generated.  ... 
doi:10.31142/ijtsrd11670 fatcat:jg5srzjnwzadfdyophhelha4li

Discovering Maximal Frequent Itemset using Association Array and Depth First Search Procedure with Effective Pruning Mechanisms

K. Sumathi, S. Kannan, K. Nagarajan
2013 International Journal of Computer Applications  
The first step of association rule mining is finding out all frequent itemsets. Generation of reliable association rules are based on all frequent itemsets found in the first step.  ...  The proposed algorithm GenMFI takes vertical tidset representation of the database and removes all the non-maximal frequent item-sets to get exact set of MFI directly.  ...  In addition, this method also provides an efficient mechanism to construct the maximal frequent candidate itemsets. The proposed approach focuses on Mining Maximal Frequent Itemset Generation.  ... 
doi:10.5120/13306-0799 fatcat:rmswbzx3gzfejb5laser34qbzy

Towards Scalable Algorithm for Closed Itemset Mining in High-Dimensional Data

Fatimah Audah Md. Zaki, Nurul Fariza Zulkurnain
2017 Indonesian Journal of Electrical Engineering and Computer Science  
Therefore, as the solution, the concept of closed frequent itemset was introduced that is lossless and condensed representation of all the frequent itemsets and their corresponding supports.  ...  <p>Mining frequent itemsets from large dataset has a major drawback in which the explosive number of itemsets requires additional mining process which might filter the interesting ones.  ...  The closure checking method and pruning strategy applied have resulted to an efficient and scalable algorithm.  ... 
doi:10.11591/ijeecs.v8.i2.pp487-494 fatcat:zihsrmbg4rctpn3psyfskxypza

Coherent closed quasi-clique discovery from large dense graph databases

Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Karypis
2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06  
Frequent coherent subgraphs can provide valuable knowledge about the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large dense graph databases  ...  Meanwhile, we devise an efficient closure checking scheme to facilitate the discovery of only closed quasi-cliques. We also develop a coherent closed quasi-clique mining algorithm, Cocain 1 .  ...  Tung and Xifeng Yan for their kind help.  ... 
doi:10.1145/1150402.1150506 dblp:conf/kdd/ZengWZK06 fatcat:ffzyda6usvbdbghcsuttxurm34

Mining globally distributed frequent subgraphs in a single labeled graph

Xing Jiang, Hui Xiong, Chen Wang, Ah-Hwee Tan
2009 Data & Knowledge Engineering  
Recent years have observed increasing efforts on graph mining and many algorithms have been developed for this purpose.  ...  However, most of the existing algorithms are designed for discovering frequent subgraphs in a set of labeled graphs only.  ...  Given two vertices of P's instance graph, v p1 and v p2 , and two vertices of Q's instance graph, v q1 and v q2 , where v q1 is generated from v p1 and v q2 is generated based on v p2 , if v p1 and v p2  ... 
doi:10.1016/j.datak.2009.04.008 fatcat:azrzv5cgfnekxmzrbbv6vexfhi

EBPA: An efficient data structure for frequent closed itemset mining

C. Vajiramedhin, J. Werapun
2013 Applied Mathematical Sciences  
In closed itemset mining, the process of mining from a large transaction database directly often leads to inefficient space and time.  ...  Practically, many data structures were proposed to maintain valuable data for frequent closed itemset mining (FCIM), while each data structure has its own advantages and disadvantages.  ...  EBPA: an efficient data structure for frequent closed itemset mining  ... 
doi:10.12988/ams.2013.13135 fatcat:qrmnxy62ifdhdfi6tpfckat2sa

Using attribute value lattice to find closed frequent itemsets

Tsau Y. Lin, Xiaohua T. Hu, Eric Louie, Belur V. Dasarathy
2003 Data Mining and Knowledge Discovery: Theory, Tools, and Technology V  
In the new method, we argue that vertical data representation and attribute value lattice can find all closed frequent itemsets efficiently, thus greatly improve the efficiency of association rule mining  ...  Finding all closed frequent itemsets is a key step of association rule mining since the non-redundant association rule can be inferred from all the closed frequent itemsets.  ...  In a vertical mining approach, there is usually no distinct candidate generation and support counting phase like in Apriori. Rather, counting is simultaneous with generation.  ... 
doi:10.1117/12.486732 dblp:conf/dmkdttt/LinHL03 fatcat:edalsfypgneafg23z422q3vjra

Proposing An Efficient Method For Frequent Pattern Mining

Vaibhav Kant Singh, Vijay Shah, Yogendra Kumar Jain, Anupam Shukla, A.S. Thoke, Vinay KumarSingh, Chhaya Dule, Vivek Parganiha
2008 Zenodo  
This paper proposes the use of both upward and downward closure property for the extraction of frequent item sets which reduces the total number of scans required for the generation of Candidate Sets.  ...  The previous approaches applied to generate frequent set generally adopt candidate generation and pruning techniques for the satisfaction of the desired objective.  ...  L.P.Pateria and Professor and Head Mathematics, Former Dean Faculty of Science, Founder Fellow International Academy of Physical Science (Allahabad) Dr. S.P. Singh G.G.  ... 
doi:10.5281/zenodo.1079632 fatcat:m6rffdsuive7dmv7dbowalhh64

Using a Hash-Based Method for Apriori-Based Graph Mining [chapter]

Phu Chien Nguyen, Takashi Washio, Kouzou Ohara, Hiroshi Motoda
2004 Lecture Notes in Computer Science  
The problem of discovering frequent subgraphs of graph data can be solved by constructing a candidate set of subgraphs first, and then, identifying within this candidate set those subgraphs that meet the  ...  In Apriori-based graph mining, to determine candidate subgraphs from a huge number of generated adjacency matrices is usually the dominating factor for the overall graph mining performance since it requires  ...  As can be seen from Table 1 , AGM-Hash efficiently reduces the number of adjacency matrices generated by the joining operation before passing them to the step of checking the downward closure property  ... 
doi:10.1007/978-3-540-30116-5_33 fatcat:soxmheumcja6hicfw7jyoxvwq4

A New MFI Mining Algorithm with effective Pruning Mechanisms

K. Sumathi, S. Kannan, K. Nagarajan
2012 International Journal of Computer Applications  
The proposed algorithm takes vertical tidset representation of the database and removes all the non-maximal frequent item-sets to get exact set of MFI directly.  ...  Mining of frequent patterns is a basic problem in data mining applications.  ...  Maximal frequent itemset mining is efficient in terms of time and space when compared to frequent itemsets and closed frequent itemsets because frequent ietmsets and closed frequent itemsets are subsets  ... 
doi:10.5120/5549-7617 fatcat:w5r4jtaulrabfh4qrglxhf3oby
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