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  1. 1
    Framework for mining XML format business process log data

    Framework for mining XML format business process log data by Ang, Jin Sheng

    Published 2024
    “…Therefore, a lot of frequent subtree mining (FSM) algorithms and methods were developed to get information from semi-structured data specifically data with hierarchical nature. …”
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  2. 2
    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…This research employed a modified version of the Design Science Research Methodology (DSRM), streamlined into five stages: problem identification, theoretical study, framework development, evaluation, and reporting. …”
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  3. 3
    Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno

    Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno by Karno, Md Razib

    Published 2015
    “…The data mining technique was adopted to explore the relationship among statistically patterned and clustered bibliographic data. …”
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  4. 4
    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
    “…These data are processed and stored in appropriate formats in a MySQL server database. 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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  5. 5
    An ensemble learning method for spam email detection system based on metaheuristic algorithms

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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  6. 6
    Evaluation of Formation Damage from Transient Pressure Analysis: Unsteady State Skin Factor

    Evaluation of Formation Damage from Transient Pressure Analysis: Unsteady State Skin Factor by El-Khatib, Noaman A.F.

    Published 2011
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  7. 7
    Multi-agent and artificial neural networks prediction framework development for stock investment strategy

    Multi-agent and artificial neural networks prediction framework development for stock investment strategy by Phang, Wai San

    Published 2016
    “…WMA comprises of an algorithm for web mining which enables it to mine and extract semi-structured information and create new structured information using ontology. …”
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  8. 8
    Multi agent and artificial neural networks prediction framework development for stock investment strategy

    Multi agent and artificial neural networks prediction framework development for stock investment strategy by Phang, Wai San

    Published 2016
    “…WMA comprises of an algorithm for web mining which enables it to mine and extract semi-structured information and create new structured information using ontology. …”
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  9. 9
    Risk Concentration for Context Assessment (RiCCA) of SMS Messages using Danger Theory

    Risk Concentration for Context Assessment (RiCCA) of SMS Messages using Danger Theory by Kamahazira Binti Zainal

    Published 2024
    “…This RiCCA prototype is developed from Danger Theory algorithms that is Dendritic Cell Algorithm (DCA) and Deterministic Dendritic Cell Algorithm (dDCA). …”
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  10. 10
    A Threshold-Based Combination of String and Semantic Similarity Measures for Record Linkage

    A Threshold-Based Combination of String and Semantic Similarity Measures for Record Linkage by Ektefa, Mohammadreza

    Published 2011
    “…In other words, in different databases, one entity may be available in different formats. Therefore, when these databases are combined, the availability of entities in different formats causes duplication. …”
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  11. 11
    A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures

    A Systematic Approach to Transform Machine Learning Students� Performance Prediction Model into Preventive Procedures by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

    Published 2023
    “…One of the major problems an instructor/institute experiences is the thorough monitoring of students� academic progress, in a course, and instigate preventive procedures to offer additional support to the students with unsatisfactory academic progress. Educational Data Mining tools, specifically Machine learning classifiers, appear supportive to develop prediction models which forecast students� final outcome in a course. …”
    Conference Paper
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  12. 12
    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection

    Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

    Published 2015
    “…The second agent is a reliability evaluation agent that uses a recursive algorithm to predict the suitability generator based on the frequency and duration reliability indices in each state while the third agent is the storage and transfer of data between the other two agents. …”
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  13. 13
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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