Search Results - (( java implementation learning algorithm ) OR ( pattern mining efficient algorithm ))

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  1. 1
    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
    “…Over the past decade, an increasing number of efficient algorithms have been proposed to mine frequent patterns by satisfying the minimum support threshold. …”
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  2. 2
    DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database

    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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  3. 3
    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. …”
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  4. 4
    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
    “…Over the past decade, an increasing number of efficient mining algorithms have been proposed to mine the frequent patterns by satisfying a user specified threshold called minimum support (minsup). …”
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  5. 5
    Algorithms for frequent itemset mining: a literature review

    Algorithms for frequent itemset mining: a literature review by Chee, C.-H., Jaafar, J., Aziz, I.A., Hasan, M.H., Yeoh, W.

    Published 2018
    “…This paper reviews and presents a comparison of different algorithms for Frequent Pattern Mining (FPM) so that a more efficient FPM algorithm can be developed. …”
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  6. 6
    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP

    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP by Saputra, Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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  7. 7
    ELP-M2: An Efficient Model for Mining Least Patterns from Data Repository

    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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  8. 8
    Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset

    Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset by Julaily Aida, Jusoh, Wan Aezwani, Wan Abu Bakar, Mustafa, Man

    Published 2018
    “…An abundant literature has dedicated in frequent pattern mining and tremendous efficient algorithms for frequent itemset mining in the transaction database. …”
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  9. 9
    EFP-M2: Efficient model for mining frequent patterns in transactional database

    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
    An efficient fuzzy clustering algorithm for mining user session clusters on web log data

    An efficient fuzzy clustering algorithm for mining user session clusters on web log data by Mallik, M. A., Zulkurnain, Nurul Fariza

    Published 2021
    “…Client access patterns can be mined from web access log information using Web Usage Mining (WUM) techniques. …”
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  11. 11
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Dhany, Saputra

    Published 2008
    “…Efficiency and scalability on mining complete set of patterns is the challenge of sequential pattern mining. …”
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  12. 12
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
    “…Efficiency and scalability on mining complete set of patterns is the challenge of sequential pattern mining. …”
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  13. 13
    Mining Sequential Patterns Using I-PrefixSpan

    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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  14. 14
    Improving mining efficiency: A new scheme for extracting association rules

    Improving mining efficiency: A new scheme for extracting association rules by Said, Aiman Moyaid, Dominic, P D D., Abdullah, Azween

    Published 2009
    “…Extracting the association rule from this data is one of the important tasks in data mining.Most of the existing association rules in algorithms typically assume that the data set can fit in the memory.In this paper, we propose a practical and effective scheme to mine association rules from frequent patterns, called Prefixfoldtree scheme (PFT scheme).The original dataset is divided into folds, and then from each fold the frequent patterns are mined by using the tree projection approach.These frequent patterns are combined into one set and finally interestingness constraints are used to extract the association rules.The experiments will be conducted to illustrate the efficiency of our scheme.…”
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  15. 15
    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin

    Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin by Latiffah, A. Noor, Nordin, A. B.

    Published 2006
    “…Data mining can discover patterns or rules from a vast volume of data. …”
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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
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  17. 17
    Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique)

    Setting up a new Radiology Center Technology for improvement : Data mining (Image Mining Technique) by Zubir, Nazira

    Published 2016
    “…Data mining is the process of mining the hidden patterns from the huge data. …”
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  18. 18
    An efficient fuzzy C-least median clustering algorithm

    An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

    Published 2021
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  19. 19
    A web usage mining approach based on LCS algorithm in online predicting recommendation systems

    A web usage mining approach based on LCS algorithm in online predicting recommendation systems by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2008
    “…To provide online prediction efficiently, we advance an architecture for online predicting in Web Usage Mining system and propose a novel approach based on LCS algorithm for classifying user navigation patterns for predicting users' future requests. …”
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  20. 20
    Feature selection with integrated Gaussian seahorse optimization data mining for cross-border business cooperation between the Malaysian medical industry and tourism industry

    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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