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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 thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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  2. 2
    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
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  3. 3
    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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  4. 4
    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
    “…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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  5. 5
    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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  6. 6
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  7. 7
    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability

    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

    Published 2024
    “…Based on the findings, the proposed logic mining model outperformed other baseline logic mining models for all the performance metrics used in the repository dataset. …”
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  8. 8
    A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi

    A multi-layer dimension reduction algorithm for text mining of news in forex / Arman Khadjeh Nassirtoussi by Nassirtoussi, Arman Khadjeh

    Published 2015
    “…Every context requires its own customized text mining algorithms in order to achieve best results. …”
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  9. 9
    Image clustering comparison of two color segmentation techniques

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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  10. 10
    A Text Mining Algorithm Optimising the Determination of Relevant Studies

    A Text Mining Algorithm Optimising the Determination of Relevant Studies by Khashfeh M., Mahmoud M.A., Ahmad M.S.

    Published 2023
    Conference Paper
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  11. 11
    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy

    Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

    Published 2019
    “…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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  12. 12
    Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing.

    Automatic Multi-Objective Clustering Algorithm Using Hybrid Particle Swarm Optimization With Simulated Annealing. by Abubaker, Ahmad Asad

    Published 2016
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  13. 13
    Finding objects with segmentation strategy based multi robot exploration in unknown environment

    Finding objects with segmentation strategy based multi robot exploration in unknown environment by Arezoumand, Reza, Mashohor, Syamsiah, Marhaban, Mohammad Hamiruce

    Published 2013
    “…Also the algorithm using segmentation strategy is using frontier base algorithm for exploring divided area. …”
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  14. 14
    A Data Mining Approach For Developing Quality Prediction Model In Multi-Stage Manufacturing

    A Data Mining Approach For Developing Quality Prediction Model In Multi-Stage Manufacturing by Arif, Fahmi, Suryana, Nanna, Hussin, Burairah

    Published 2013
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  15. 15
    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi

    Clustering of large time-series datasets using a multi-step approach / Saeed Reza Aghabozorgi Sahaf Yazdi by Yazdi, Saeed Reza Aghabozorgi Sahaf

    Published 2013
    “…Time-series clustering is not only useful as an exploratory technique but also as a subroutine in more complex data mining algorithms. …”
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  16. 16
    Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability

    Unsupervised logic mining with a binary clonal selection algorithm in multi-unit discrete Hopfield neural networks via weighted systematic 2 satisfiability by Romli, Nurul Atiqah, Zulkepli, Nur Fariha Syaqina, Kasihmuddin, Mohd Shareduwan Mohd, Zamri, Nur Ezlin, Rusdi, Nur 'Afifah, Manoharam, Gaeithry, Mansor, Mohd. Asyraf, Jamaludin, Siti Zulaikha Mohd, Malik, Amierah Abdul

    Published 2024
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  17. 17
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  18. 18
    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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  19. 19
    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 Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

    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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  20. 20
    Hybrid ant colony optimization and genetic algorithm for rule induction

    Hybrid ant colony optimization and genetic algorithm for rule induction by Al-Behadili, Hayder Naser Khraibet, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…The AntMiner classifier is efficient, useful and commonly used for solving rulebased classification problems in data mining. …”
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