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  1. 1
    Clustering ensemble learning method based on incremental genetic algorithms

    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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  2. 2
    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
    “…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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  3. 3
    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
    “…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
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  4. 4
    Optimized feature construction methods for data summarizations of relational data

    Optimized feature construction methods for data summarizations of relational data by Sze, Florence Sia Fui

    Published 2014
    “…This thesis also presents the study of a method to improve the descriptive accuracy of DARA algorithm by generating multi-instances of summarized data. …”
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  5. 5
    A Data Mining Approach to Enhancing Birth and Death Registration Processes

    A Data Mining Approach to Enhancing Birth and Death Registration Processes by Erfan, Hasmin

    Published 2025
    “…The optimal number of clusters of clusters for birth and death data is determined as three using elbow and silhouette validation methods. …”
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  6. 6
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2009
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  7. 7
    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

    Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor by Brahim Belhaouari, samir

    Published 2008
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  8. 8
    Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

    Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model by Yaseen, Z.M., Ebtehaj, I., Bonakdari, H., Deo, R.C., Danandeh Mehr, A., Mohtar, W.H.M.W., Diop, L., El-Shafie, A., Singh, V.P.

    Published 2017
    “…The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. …”
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  9. 9
    Rule Generation Based On Structural Clustering For Automatic Question Answering

    Rule Generation Based On Structural Clustering For Automatic Question Answering by Song , Shen

    Published 2009
    “…To address these issues, an automatic structural rule generation algorithm is presented via clustering, where a center sentence-based clustering method is designed to automatically generate rules for QA systems.…”
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  10. 10
    Comparison between Market Basket Analysis and Partition Around Medoids clustering for knowledge discovering in consumer consumption pattern / Mohammad Adha Ruslan, Nurul Shahira Mohammad Ramly and Nor Hasliza Saberi

    Comparison between Market Basket Analysis and Partition Around Medoids clustering for knowledge discovering in consumer consumption pattern / Mohammad Adha Ruslan, Nurul Shahira Mo... by Ruslan, Mohammad Adha, Mohammad Ramly, Nurul Shahira, Saberi, Nor Hasliza

    Published 2019
    “…Nowadays, Knowledge Data Discovery (KOO), is an important knowledge for the industry and an organized process of understandable patterns from a large data set. The main purpose of this study are to compare the knowledge discovery between Market Basket Analysis and Partition Around Medoids and followed by to generate a customer buying pattern by using Market Basket Analysis (MBA) Algorithm and Partition Around Medoids (PAM) Clustering Algorithm. …”
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  11. 11
    Frequent patterns minning of stock data using hybrid clustering association algorithm

    Frequent patterns minning of stock data using hybrid clustering association algorithm by B., Baharudin, A., Khan, K., Khan

    Published 2009
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
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  12. 12
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…huge data is a big challenge. Clustering technique is able to find hidden patterns and to extract useful information from huge data. …”
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  13. 13
    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
    “…Identifying all frequent patterns is the most time consuming process due to a massive number of patterns generated. …”
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  14. 14
    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data

    Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data by Laxmi Lydia E., Sharmili N., Nguyen P.T., Hashim W., Maseleno A.

    Published 2023
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  15. 15
    A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube

    A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube by Al?amri R., Murugesan R.K., Almutairi M., Munir K., Alkawsi G., Baashar Y.

    Published 2023
    “…TSHC when added to Buffer?based Online Clustering for Evolving Data Stream (BOCEDS) results in a superior evolving data stream clustering algorithm. …”
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  16. 16
    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat

    A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

    Published 2021
    “…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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  17. 17
    An initial state of design and development of intelligent knowledge discovery system for stock exchange database

    An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

    Published 2004
    “…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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  18. 18
    A hybrid-based modified adaptive fuzzy inference engine for pattern classification

    A hybrid-based modified adaptive fuzzy inference engine for pattern classification by Sayeed, Md. Shohel, Ramli, Abdul Rahman, Hossen, Md. Jakir, Samsudin, Khairulmizam, Rokhani, Fakhrul Zaman

    Published 2011
    “…A TSK type fuzzy inference system is constructed by the automatic generation of membership functions and rules by the hybrid fuzzy clustering and Apriori algorithm technique, respectively. …”
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  19. 19
    Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari

    Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari by Chaudhari, Archana, Mulay, Preeti, Kumar Tiwari, Amit

    Published 2022
    “…To achieve learning from such dynamic data sources, incremental clustering algorithms are used mandatorily. This mandate has given rise to increased patents related to incremental clustering concept, which is primarily a significant part of Machine Learning field. …”
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  20. 20
    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM

    MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

    Published 2011
    “…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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