Efficient Dynamic Weighted Frequent Pattern Mining by using a Prefix-Tree

This chapter surveys the maintenance of frequent patterns in transaction datasets. It is written to be accessible to researchers familiar with the field of frequent pattern mining. The frequent pattern maintenance problem is summarized with a study on how the space of frequent patterns evolves in response to data updates. This chapter focuses on incremental and decremental maintenance. Four major types of maintenance algorithms are studied: Apriori-based, partition-based, prefix-tree-based, and conciserepresentation- based algorithms. The authors study the advantages and limitations of these algorithms from both the theoretical and experimental perspectives. Possible solutions to certain limitations are also proposed. In addition, some potential research opportunities and emerging trends in frequent pattern maintenance are also discussed.

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The Benefits of Using Prefix Tree Data Structure in Multi-Level Frequent Pattern Mining

2007 2nd International Workshop on Soft Computing Applications ◽

10.1109/sofa.2007.4318326 ◽

2007 ◽

Author(s):

Mirela Pater ◽

Daniela E. Popescu

Keyword(s):

Data Structure ◽

Pattern Mining ◽

Frequent Pattern Mining ◽

Frequent Pattern ◽

Prefix Tree ◽

Tree Data ◽

Multi Level ◽

Tree Data Structure

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Efficient frequent pattern mining based on Linear Prefix tree

Knowledge-Based Systems ◽

10.1016/j.knosys.2013.10.013 ◽

2014 ◽

Vol 55 ◽

pp. 125-139 ◽

Cited By ~ 60

Author(s):

Gwangbum Pyun ◽

Unil Yun ◽

Keun Ho Ryu

Keyword(s):

Pattern Mining ◽

Frequent Pattern Mining ◽

Frequent Pattern ◽

Prefix Tree

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Efficient single-pass frequent pattern mining using a prefix-tree

Information Sciences ◽

10.1016/j.ins.2008.10.027 ◽

2009 ◽

Vol 179 (5) ◽

pp. 559-583 ◽

Cited By ~ 79

Author(s):

Syed Khairuzzaman Tanbeer ◽

Chowdhury Farhan Ahmed ◽

Byeong-Soo Jeong ◽

Young-Koo Lee

Keyword(s):

Pattern Mining ◽

Frequent Pattern Mining ◽

Frequent Pattern ◽

Single Pass ◽

Prefix Tree

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An efficient frequent pattern mining algorithm using a highly compressed prefix tree

Intelligent Data Analysis ◽

10.3233/ida-192645 ◽

2019 ◽

Vol 23 ◽

pp. 153-173

Author(s):

Xiaolin Zhu ◽

Yongguo Liu

Keyword(s):

Pattern Mining ◽

Frequent Pattern Mining ◽

Frequent Pattern ◽

Prefix Tree ◽

Mining Algorithm

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An Adaptive Data Distribution Through Tree Rules in Frequent Pattern Mining

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit183894 ◽

2018 ◽

pp. 300-305

Keyword(s):

Information Sharing ◽

Pattern Mining ◽

Data Distribution ◽

Frequent Pattern Mining ◽

Frequent Pattern ◽

General Development ◽

Secure Information ◽

Evaluation Parameters ◽

Secure Information Sharing

Information sharing among the associations is a general development in a couple of zones like business headway and exhibiting. As bit of the touchy principles that ought to be kept private may be uncovered and such disclosure of delicate examples may impacts the advantages of the association that have the data. Subsequently the standards which are delicate must be secured before sharing the data. In this paper to give secure information sharing delicate guidelines are bothered first which was found by incessant example tree. Here touchy arrangement of principles are bothered by substitution. This kind of substitution diminishes the hazard and increment the utility of the dataset when contrasted with different techniques. Examination is done on certifiable dataset. Results shows that proposed work is better as appear differently in relation to various past strategies on the introduce of evaluation parameters.

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