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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
    Discovering association rules for mining images datasets: a proposal

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

    Published 2005
    “…A synthetic image set containing geometric shapes will generate to test the initial algorithm implementation. The experiments results show that there is promise in image mining based on content. …”
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  3. 3
    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. …”
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  4. 4
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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  5. 5
    Frequent Lexicographic Algorithm for Mining Association Rules

    Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

    Published 2005
    “…The scale-up experiment showed that the proposed algorithm is more scalable than the other existing algorithms. …”
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  6. 6
    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network

    Y-type Random 2-satisfiability In Discrete Hopfield Neural Network by Guo, Yueling

    Published 2024
    “…The proposed algorithm and mutation mechanism showed optimal performances as compared to the existing algorithms. …”
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  7. 7
    Mining least relational patterns from multi relational tables

    Mining least relational patterns from multi relational tables by Selamat, Siti Hairulnita, Mat Deris, Mustafa, Mamat, Rabiei, Bakar, Zuriana Abu

    Published 2005
    “…Results from the implementation reveal that the algorithm is capable of mining rare item in multi relational tables.…”
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  8. 8
    A novel approach to data mining using simplified swarm optimization

    A novel approach to data mining using simplified swarm optimization by Wahid, Noorhaniza

    Published 2011
    “…In this thesis, a novel Simplified Swarm Optimization (SSO) algorithm is proposed as a rule-based classifier and for feature selection. …”
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  9. 9
    Scalable approach for mining association rules from structured XML data

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  10. 10
    RARE: mining colossal closed itemset in high dimensional data

    RARE: mining colossal closed itemset in high dimensional data by Md Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza

    Published 2018
    “…With that, this paper investigated the strategies implemented in both row and column enumerationbased algorithms, hence proposing the RARE; a breadth-first bottom-up row-enumeration algorithm, in mining colossal closed itemsets in high-dimensional data…”
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  11. 11
    An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis

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

    Published 2016
    “…In conclusion, the proposed algorithm is able to overcome the rare item issue by implementing covariance based support value normalization and high computational costs issue by implementing indexing enumeration tree structure.Future work of this study should focus on rule interpretation to generate more human understandable rule by novice in data mining. …”
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  12. 12
    Mining association rules from structured XML data

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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  13. 13
    Case Slicing Technique for Feature Selection

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

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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  14. 14
    The semantics of norms mining in multi-agent systems

    The semantics of norms mining in multi-agent systems by Ahmed Mahmoud, Moamin, Ahmad, Mohd Sharifuddin, Ahmad, Azhana, Mohd Yusoff, Mohd Zaliman, Mustapha, Aida

    “…We then present an algorithm of the norms mining operation and demonstrate the success of the technique in detecting the potential norms. …”
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  15. 15
    Training functional link neural network with ant lion optimizer

    Training functional link neural network with ant lion optimizer by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

    Published 2020
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  16. 16
    Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm

    Logic Mining Approach: Shoppers’ Purchasing Data Extraction via Evolutionary Algorithm by Mohd Kasihmuddin, Mohd Shareduwan, Abdul Halim, Nur Shahira, Mohd Jamaludin, Siti Zulaikha, Mansor, Mohd. Asyraf, Alway, Alyaa, Zamri, Nur Ezlin, Azhar, Siti Aishah, Marsani, Muhammad Fadhil

    Published 2023
    “…The simulation suggested that the proposed model outperformed the existing model in doing logic mining for the online shoppers dataset.…”
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  17. 17
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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  18. 18
    Obligation and Prohibition Norms Mining Algorithm for normative multi-agent systems

    Obligation and Prohibition Norms Mining Algorithm for normative multi-agent systems by Mahmoud M.A., Ahmad M.S., Ahmad A., Yusoff M.Z.M., Mustapha A., Hamid N.H.A.

    Published 2023
    “…In this paper, we present our proposed algorithm to detect the obligation and prohibition norms which we called the Obligation and Prohibition Norms Mining algorithm (OPNM). …”
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  19. 19
    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network

    Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network by Kang, Miew How

    Published 2016
    “…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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  20. 20
    Using fuzzy association rule mining in cancer classification

    Using fuzzy association rule mining in cancer classification by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

    Published 2011
    “…At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. …”
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