Search Results - (( pattern mining algorithm ) OR ((( pattern _ algorithm ) OR ( patterns growth algorithm ))))

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  1. 1

    DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database by Zailani, Abdullah, Herawan, Tutut, Noraziah, Ahmad, Mustafa, Mat Deris

    Published 2012
    “…Therefore, in this paper we introduce an efficient algorithm called Dynamic Frequent Pattern Growth (DFP-Growth) to mine the frequent patterns from dynamic database. …”
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  2. 2

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

    Published 2010
    “…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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  3. 3

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

    Published 2010
    “…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows.First, it compresses the database representing frequent items into a frequent-pattern tree, or FP-tree, which retains the itemset association information. …”
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  4. 4

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

    Published 2011
    “…An interest solution is to design an approach that without generating candidate is able to mine frequent patterns. Results: An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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    Article
  5. 5

    ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository by Zailani, Abdullah, Amir, Ngah, Herawan, Tutut, Noraziah, Ahmad, Siti Zaharah, Mohamad, Abdul Razak, Hamdan

    Published 2017
    “…Therefore, in this paper we proposed a complete model for mining least patterns known as Efficient Least Pattern Mining Model (ELP-M2) with LP-Tree data structure and LP-Growth algorithm. …”
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    Book Chapter
  6. 6

    Discovering Pattern in Medical Audiology Data with FP-Growth Algorithm by G. Noma, Nasir, Mohd Khanapi, Abd Ghani

    Published 2012
    “…We use frequent pattern growth (FP-Growth) algorithm in the data processing step to build the FP-tree data structure and mine it for frequents itemsets. …”
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  7. 7

    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
  8. 8

    The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

    Published 2007
    “…This , paper discusses the development of data mining and pattern recognition algorithm to handle the complexity of hyperspectral remote sensing images in Geographical Information Systems environment. …”
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  9. 9

    EFP-M2: Efficient model for mining frequent patterns in transactional database by Herawan, Tutut, Noraziah, Ahmad, Zailani, Abdullah, Mustafa, Mat Deris, H. Abawajyd, Jemal

    Published 2012
    “…Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. …”
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  10. 10

    A Scalable Algorithm for Constructing Frequent Pattern Tree by Noraziah, Ahmad, Herawan, Tutut, Zailani, Abdullah, Mustafa, Mat Deris

    Published 2014
    “…The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. …”
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    Article
  11. 11

    Mining dense data: Association rule discovery on benchmark case study by Bakar, W.A.W.A., Saman, M.D.M., Abdullah, Z., Jalil, M.A., Herawan, T.

    Published 2016
    “…In this article, we present comparison result between Apriori and FP-Growth algorithm in generating association rules based on a benchmark data from frequent itemset mining data repository. …”
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    Article
  12. 12

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

    Published 2020
    “…One such pre-processing algorithm in EDM is clustering. It is a widely used method in data mining to discover unique patterns in underlying data. …”
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    Thesis
  13. 13

    Development of a Web Access Control Technique Based User Access Behavior by Abdelrahman, Selmaelsheikh

    Published 2004
    “…A set of algorithms is used for mining user access behavior, preprocessing tasks for data preparation, association rules for defining the rules that describe the correlation between web user access transaction entries patterns, and sequential pattern discovery for finding the sequences of the web user access transaction entries pattern using Prefixspan (Pattern growth via frequent sequence lattice) algorithms. …”
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    Thesis
  14. 14

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

    Published 2007
    “…Most of the previous works explore Apriori approach which is not efficient in mining plentiful and long patterns. In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. …”
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  15. 15

    Feature selection with integrated Gaussian seahorse optimization data mining for cross-border business cooperation between the Malaysian medical industry and tourism industry by Ma, Yuaner, Jabar, Juhaini, Abdul Aziz, Nor Azah

    Published 2023
    “…The integrated GSH-DM model then applies the Gaussian Seahorse Optimization algorithm to optimize the data mining process, enhancing the accuracy and efficiency of pattern discovery. the GSH-DM model, this study aims to uncover hidden patterns, relationships, and predictive models that can guide decision-making and strategy development for cross-border business cooperation. …”
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    Article
  16. 16

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

    Published 2008
    “…In this paper, we propose an improvement of pattern growth-based PrefixSpan algorithm, called I-PrefixSpan. …”
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    Citation Index Journal
  17. 17

    Identifying Relationship between Hearing loss Symptoms and Pure-tone Audiometry Thresholds with FP-Growth Algorithm by G. Noma, Nasir, Mohd Khanapi, Abd Ghani, Mohamad Khir , Abdullah

    Published 2013
    “…The purpose of this study was to find the relationship that exists between pure-tone audiometry threshold values and hearing loss symptoms in a medical datasets of 339 hearing loss patients using association rule mining algorithm. FP-Growth (Frequent Pattern) algorithm is employed for this purpose to generate itemsets given 0.2 (20%) as the support threshold value and 0.7 (70%) as the confidence value for association rule generation. …”
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    Article
  18. 18

    Detecting Critical Least Association Rules In Medical Databases by Herawan, Tutut

    Published 2010
    “…We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. …”
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    Article
  19. 19

    An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

    Published 2016
    “…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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    Thesis
  20. 20

    Modifying iEclat algorithm for infrequent patterns mining by Julaily Aida, J., Mustafa, M.

    Published 2018
    “…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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