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  1. 1
    Genetic Algorithm for Web Data Mining

    Genetic Algorithm for Web Data Mining by Loo, Kevin Teow Aik

    Published 2001
    “…By doing so, it could assist the process of data mining for information in the World Wide Web. This study used a prototype program based on genetic algorithm to manipulate the initial set of data. …”
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  2. 2
    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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  3. 3
    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
    “…Because of these circumstances data mining is extremely important to get valuable data from WWW.Clustering data mining is the process of putting together meaning-full or use-full similar object into one group. …”
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  4. 4
    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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  5. 5
    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
    “…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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  6. 6
    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
    “…Then, the mapping percentages between the predefined and produced clusters are used to assess the performance of the proposed algorithm. …”
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  7. 7
    Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar

    Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar by Mokhtar, Nurul Zafirah

    Published 2016
    “…The cluster detection algorithm searches for clusters of data which are similar to one another by using similarity measures. …”
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  8. 8
    Tree-based contrast subspace mining method

    Tree-based contrast subspace mining method by Florence Sia Fui Sze

    Published 2020
    “…The tree-based method begins with feature selection phase which finds relevant features and followed by contrast subspace search phase to search contrast subspaces from the relevant features, accordance to the tree-based likelihood contrast scoring function. Genetic algorithm has been widely used to find global solution to optimization and search problem. …”
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  9. 9
    Automatic clustering of gene ontology by genetic algorithm

    Automatic clustering of gene ontology by genetic algorithm by Othman, Razib M., Deris, Safaai, Zakaria, Zalmiyah, Illias, Rosli M., Mohamad, Saberi M.

    Published 2006
    “…Additionally, deciding the number k of clusters to use is not easily perceived and is a hard algorithmic problem. …”
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  10. 10
    Advanced data mining techniques for landslide susceptibility mapping

    Advanced data mining techniques for landslide susceptibility mapping by Ibrahim, M.B., Mustaffa, Z., Balogun, A.-L., Hamonangan Harahap, I.S., Ali Khan, M.

    Published 2021
    “…SVM, RT, and NBM algorithms were used to produce predicted datasets from the training datasets. …”
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  11. 11
    Prediction of college student academic performance using data mining techniques.

    Prediction of college student academic performance using data mining techniques. by Abd Jalil, Azura, Mustapha, Aida, Santa, Dzulizah, Zain, Nurul Zaiha, Radwan, Rizalina

    Published 2013
    “…The classification algorithms used are the Decision Tree, Naïve Bayesian, and Multilayer Perception with the highest classification accuracy by the Naive Bayes algorithm with accuracy of 95.3%. …”
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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
    Classification of students' performance in computer programming course according to learning style

    Classification of students' performance in computer programming course according to learning style by Norwawi N.M., Abdusalam S.F., Hibadullah C.F., Shuaibu B.M.

    Published 2024
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  14. 14
    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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  15. 15
    An improved ACS algorithm for data clustering

    An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

    Published 2020
    “…To improve the ACOC, this study proposes a modified ACOC, called M-ACOC, which has a modification rate parameter that controls the convergence of the algorithm. Comparison of the performance of several common clustering algorithms using real-world datasets shows that the accuracy results of the proposed algorithm surpasses other algorithms.…”
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  16. 16
    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman

    Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

    Published 2013
    “…Six Y-STR data sets were used as a benchmark to evaluate the performances of the algorithm against the other eight partitional clustering algorithms. …”
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  17. 17
    Adaptive firefly algorithm for hierarchical text clustering

    Adaptive firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim

    Published 2016
    “…As search engine operates on Internet content that is constantly being updated, there is a need for a clustering algorithm that offers automatic grouping of items without prior knowledge on the collection. …”
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  18. 18
    Determining number of clusters using firefly algorithm with cluster merging for text clustering

    Determining number of clusters using firefly algorithm with cluster merging for text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2015
    “…Such a scenario requires a dynamic text clustering method that operates without initial knowledge on a data collection.In this paper, a dynamic text clustering that utilizes Firefly algorithm is introduced.The proposed, aFAmerge, clustering algorithm automatically groups text documents into the appropriate number of clusters based on the behavior of firefly and cluster merging process. …”
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  19. 19
    A customized non-exclusive clustering algorithm for news recommendation systems

    A customized non-exclusive clustering algorithm for news recommendation systems by Ibrahim, Hamidah, Sidi, Fatimah, Mustapha, Aida, Darvishy, Asghar

    Published 2019
    “…An experiment is carried out using a real dataset which is collected from the news websites. …”
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  20. 20
    Modeling Primary School Student Academic Performance Using Data Mining Technique

    Modeling Primary School Student Academic Performance Using Data Mining Technique by Muhamad, Mat Yaacub

    Published 2011
    “…The dataset consists of 6 attributes that are gender and 5 core subjects namely Pemahaman, Penulisan, Sciences, English and Mathematics which were then grouped into excellent, fair and weak group and was mined using association rules technique based on Apriori algorithm to find interesting rules which can influence student academic performance. …”
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