Search Results - (( java application mining algorithm ) OR ( knowledge segmentation clustering algorithm ))

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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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  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
    Data stream clustering by divide and conquer approach based on vector model

    Data stream clustering by divide and conquer approach based on vector model by Khalilian, Madjid, Mustapha, Norwati, Sulaiman, Nasir

    Published 2016
    “…The continuous effort on data stream clustering method has one common goal which is to achieve an accurate clustering algorithm. …”
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  5. 5
    KopiCulture: Unveiling Customer Loyalty in Malaysia's Coffee Market through Clustering Algorithms for Local Cafe Insights

    KopiCulture: Unveiling Customer Loyalty in Malaysia's Coffee Market through Clustering Algorithms for Local Cafe Insights by Tuan Norhafizah, Tuan Zakaria, Che Ku Nuraini, Che Ku Mohd

    Published 2024
    “…This study aims to identify customer loyalty patterns in the Malaysian coffee market, focusing on the Malaysia Starbucks customer survey dataset. Using clustering algorithms such as KMeans, KMeans with Principal Component Analysis (PCA), single linkage, complete linkage, DBScan, and DBScan in conjunction with PCA, we identify distinct customer segments based on loyalty patterns. …”
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  6. 6
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…The system trains the NN on previously labelled data, and its knowledge is used to calculate the core online-offline clustering block error. …”
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  7. 7
    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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  8. 8
    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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  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 detailed description on unsupervised heterogeneous anomaly based intrusion detection framework

    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework by Udzir, Nur Izura, Hajamydeen, Asif Iqbal

    Published 2019
    “…To accomplish this, a current segment (clustering) has been used and a few new parts (filtering, aggregating and feature analysis) have been presented. …”
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  11. 11
    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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