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  1. 1

    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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  2. 2

    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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  3. 3

    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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    Thesis
  4. 4

    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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    Final Year Project
  5. 5

    Using unique-prime-factorization theorem to mine frequent patterns without generating tree by Tohidi, Hossein, Ibrahim, Hamidah

    Published 2011
    “…Our algorithm works based on prime factorization and is called Prime Factor Miner (PFM). …”
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    Article
  6. 6

    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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    Article
  7. 7

    Propositional satisfiability algorithm to find minimal reducts for data mining by Bakar, A.A., Sulaiman, M.N., Othman, M., Selamat, M.H.

    Published 2002
    “…An algorithm in finding minimal reducts based on Prepositional Satisfiability (SAT) algorithm is proposed. …”
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    Article
  8. 8

    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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    Book Chapter
  9. 9

    A semi-apriori algorithm for discovering the frequent itemsets by Fageeri, S.O., Ahmad, R., Baharudin, B.B.

    Published 2014
    “…Frequent itemsets generation produce extremely large numbers of generated itemsets that make the algorithms inefficient. …”
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    Conference or Workshop Item
  10. 10

    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…Total rules number, rules length and rules accuracy for the generation rules are recorded. The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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    Thesis
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    Combining object-based classification and data mining algorithm to classify urban surface materials from worldview-2 satellite image by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2014
    “…In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. …”
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    Conference or Workshop Item
  13. 13

    An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

    Published 2019
    “…The generation of rule is considered a crucial process in data mining and the generated rules are in a huge number. …”
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    Thesis
  14. 14

    Discovering association rules for mining images datasets: a proposal by Hamzah, Azizi, O. K. Rahmat, Rahmita Wirza, Sulaiman, Md. Nasir

    Published 2005
    “…The experiments results show that there is promise in image mining based on content. Finally, the association rules will determine using an adaptation of the Apriori Algorithm. …”
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    Conference or Workshop Item
  15. 15

    Role Minimization As An Optimization Metric In Role Mining Algorithms : A Literature Review by Ahmad, Rabiah, Abd Hamid, Nazirah, Selamat, Siti Rahayu

    Published 2018
    “…A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining.The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the userpermission assignment.To solve this problem,the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set.Eventually,the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles,sizes of userassignment and permission-assignment and Weighted Structural Complexity.Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric.This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles. …”
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    Article
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    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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    Article
  19. 19

    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
    “…Social media mining is the process of collecting large datasets from user-generated content and extracting and analyzing social media interactions to recognize meaningful patterns in individual and social behavior. …”
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    Article
  20. 20

    Combining data mining algorithm and object-based image analysis for detailed urban mapping of hyperspectral images by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi, Mansor, Shattri, Ahmad, Noordin

    Published 2014
    “…The images were used to explore the combined performance of a data mining (DM) algorithm and object-based image analysis (OBIA). …”
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    Article