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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
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    Thesis
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  2. 2
    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
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  3. 3
    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
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions

    Machine Learning Algorithm for Malware Detection: Taxonomy, Current Challenges, and Future Directions by Gorment N.Z., Selamat A., Cheng L.K., Krejcar O.

    Published 2024
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  5. 5
    Designing a new model to detect Trojan Horse based on knowledge discovery and data mining

    Designing a new model to detect Trojan Horse based on knowledge discovery and data mining by Areej Mustafa Khlaif Abuzaid

    Published 2024
    thesis::master thesis
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  6. 6
    Mining Sequential Patterns Using I-PrefixSpan

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

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  7. 7
    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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    Final Year Project / Dissertation / Thesis
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  8. 8
    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works

    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

    Published 2023
    Conference Paper
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  9. 9
    Mining Sequential Patterns using I-PrefixSpan

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

    Published 2008
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    Citation Index Journal
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  10. 10
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  11. 11
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  12. 12
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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  13. 13
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
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  14. 14
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Ismail, Saidatul Akmar, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
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  15. 15
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
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  16. 16
    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data

    A Systematic Review of Anomaly Detection within High Dimensional and Multivariate Data by Suboh, Syahirah, Abdul Aziz, Izzatdin, Shaharudin, Shazlyn Milleana, Akmar Ismail, Saidatul, Mahdin, Hairulnizam

    Published 2023
    “…Overall, most methods have shown an excellent ability to tackle the curse of dimensionality and multivariate features to perform anomaly detection. Moreover, a comparison of each algorithm for anomaly detection is also provided to produce a better algorithm. …”
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    Article
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  17. 17
    Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System

    Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Alraddadi, Abdulaziz Saleh, Aldhaqm, Arafat

    Published 2021
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  18. 18
    Cyberbullying detection and prevention: Data mining in social media

    Cyberbullying detection and prevention: Data mining in social media by Sultan D., Suliman A., Toktarova A., Omarov B., Mamikov S., Beissenova G.

    Published 2023
    Conference Paper
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  19. 19
    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
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  20. 20
    Enhanced mechanism to handle missing data of Hadith classifier

    Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

    Published 2011
    “…Tree structured modeling is a data mining technique used to recursively partition a data set into relatively homogeneous subgroups in order to make more accurate predictions on the future instances. …”
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    Proceeding Paper
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