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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The proposed method, XiFLEX has been implemented using two different techniques (java based & XQuery) and compared with the original FLEX algorithm in its basic implementation and the Apriori algorithm for frequent patterns generation. …”
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  2. 2
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  3. 3
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  4. 4
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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  5. 5
    Efficient prime-based method for interactive mining of frequent patterns.

    Efficient prime-based method for interactive mining of frequent patterns. by Mohammad Hossein, Nadimi Shahraki, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2011
    “…In this paper, we propose a new method based on prime number and its characteristics mainly for interactive mining of frequent patterns. …”
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  6. 6
    Prime-based method for interactive mining of frequent patterns

    Prime-based method for interactive mining of frequent patterns by Nadimi-Shahraki, Mohammad-Hossein

    Published 2010
    “…Then, the proposed method is developed based on the architecture such that the mining model is constructed once, and it can be frequently mined by various minsup. …”
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  7. 7
    A numerical method for frequent pattern mining

    A numerical method for frequent pattern mining by Mustapha, Norwati, Nadimi-Shahraki, Mohammad-Hossein, Mamat, Ali, Sulaiman, Md. Nasir

    Published 2009
    “…In this paper, an efficient numerical method for mining frequent patterns is proposed. This method is based on prime number characteristics to generate all frequent patterns by using maximal frequent ones. …”
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  8. 8
    Optimizing Tree-Based Contrast Subspace Mining Using Genetic Algorithm

    Optimizing Tree-Based Contrast Subspace Mining Using Genetic Algorithm by Sia, Florence Fui Sze, Rayner Alfred

    Published 2022
    “…Recently, tree-based contrast subspace mining method has been introduced to find contrast subspace in numerical data set effectively. …”
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  9. 9
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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  10. 10
    Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.]

    Exploratory analysis with association rule mining algorithms in the retail industry / Alaa Amin Hashad ... [et al.] by Hashad, Alaa Amin, Khaw, Khai Wah, Alnoor, Alhamzah, Chew, Xin Ying

    Published 2024
    “…The proposed method is based on comparing two algorithms: Apriori and Frequent Pattern Growth (FP- Growth). …”
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  11. 11
    A Rough-Apriori Technique in Mining Linguistic Association Rules

    A Rough-Apriori Technique in Mining Linguistic Association Rules by Choo, Yun Huoy, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

    Published 2008
    “…It uses the rough membership function to capture the linguistic interval before implementing the Apriori algorithm to mine interesting association rules. The performance of conventional quantitative association rules mining algorithm with Boolean reasoning as the discretization method was compared to the proposed technique and the fuzzy-based technique. …”
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  12. 12
    Data mining based damage identification using imperialist competitive algorithm and artificial neural network

    Data mining based damage identification using imperialist competitive algorithm and artificial neural network by Gordan, Meisam, Razak, Hashim Abdul, Ismail, Zubaidah, Ghaedi, Khaled

    Published 2018
    “…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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  13. 13
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  14. 14
    A partition based feature selection approach for mixed data clustering / Ashish Dutt

    A partition based feature selection approach for mixed data clustering / Ashish Dutt by Ashish , Dutt

    Published 2020
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  15. 15
    Social media mining: a genetic based multiobjective clustering approach to topic modelling

    Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

    Published 2021
    “…However, less works have been conducted in applying multiobjective based algorithm for topic extraction. Most of these algorithms are not optimized, even if they are, they are only optimized by using a single objective method and may underperform when solving real-world problems which are typically multi-objectives in nature. …”
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  16. 16
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  17. 17
    A frequent pattern mining algorithm based on FP-growth without generating tree

    A frequent pattern mining algorithm based on FP-growth without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2010
    “…Our algorithm works based on prime factorization, and is called Frequent Pattern-Prime Factorization (FPPF).…”
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  18. 18
    A frequent pattern mining algorithm based on FP-growth without generating tree

    A frequent pattern mining algorithm based on FP-growth without generating tree by Tohid, Hossein, Ibrahim, Hamidah

    Published 2010
    “…It then divides the compressed database into a set of conditional databases (a special kind of projected database), each associated with one frequent item or pattern fragment, and mines each such database separately.For a large database, constructing a large tree in the memory is a time consuming task and increase the time of execution.In this paper we introduce an algorithm to generate frequent patterns without generating a tree and therefore improve the time complexity and memory complexity as well.Our algorithm works based on prime factorization, and is called Frequent Pattern- Prime Factorization (FPPF).…”
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  19. 19
    Frequent itemset mining using graph theory / Mohammad Arsyad Mohd Yakop

    Frequent itemset mining using graph theory / Mohammad Arsyad Mohd Yakop by Mohd Yakop, Mohammad Arsyad

    Published 2017
    “…The Directed Acyclic Graph in High Dimensional Dataset Mining (DAGHDDM) is a graph-based mining algorithm that represents itemsets in complete graph before FIM takes place. …”
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  20. 20
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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    Monograph
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