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  1. 1
    A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment

    A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment by Rajoo, S, Magalingam, P, Idris, NB, Samy, GN, Maarop, N, Shanmugam, B, Perumal, S

    Published 2024
    Proceedings Paper
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  2. 2
    Intent-IQ: customer’s reviews intent recognition using random forest algorithm

    Intent-IQ: customer’s reviews intent recognition using random forest algorithm by Mazlan, Nur Farahnisrin, Ibrahim Teo, Noor Hasimah

    Published 2025
    “…Intent-IQ is a web application system which allows users to input Shopee product link and it leads to the intent classification, where the reviews can be classified into its intent categories such as praise, complaint and suggestion. …”
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  3. 3
    Named entity recognition using a new fuzzy support vector machine.

    Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

    Published 2008
    “…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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  4. 4
    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  5. 5
    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun

    Intelligent agent for e-commerce using genetic algorithm / Kok Sun Sun by Kok , Sun Sun

    Published 2000
    “…In addition, the system is developed using the developing tools that are essential in web applications, namely. web server, database server, system server and web programming tools such as ASP and Visual Basic. …”
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  6. 6
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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    Final Year Project
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  7. 7
    Support Vector Machines (SVM) in Test Extraction

    Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

    Published 2006
    “…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. Each word in the particular document is processed by both algorithms to determine its actual occurrence in the document by which it will first be clustered or grouped into categories based on parts of speech (verb, noun, adjective) which is done by K-Means, then later processed by SVM to determine the actual occurrence of each word in each of the cluster, taking into account whether the words have similar meanings with otherwords in the subsequent cluster. …”
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  8. 8
    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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  9. 9
    Entiment analysis of public perception on AI chatbots using Support Vector Machine (SVM) algoritm / Tuan Nur Azlina Tuan Ibrahim

    Entiment analysis of public perception on AI chatbots using Support Vector Machine (SVM) algoritm / Tuan Nur Azlina Tuan Ibrahim by Tuan Ibrahim, Tuan Nur Azlina

    Published 2024
    “…Facing challenges with existing methods, the Support Vector Machine (SVM) algorithm is employed for its proficiency in handling textual data. …”
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  10. 10
    Web Usage Mining Using GSP Algorithm: A Study on Sultanah Bahiyah Library Online Databases

    Web Usage Mining Using GSP Algorithm: A Study on Sultanah Bahiyah Library Online Databases by Hazzaimeh, Yousef Abd-AlMohdi

    Published 2008
    “…In this study web usage mining use sequential pattern technique with GSP algorithm. …”
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  11. 11
    Cryptanalytic attacks on Rivest, Shamir, and Adleman (RSA) cryptosystem: issues and challenges

    Cryptanalytic attacks on Rivest, Shamir, and Adleman (RSA) cryptosystem: issues and challenges by Abubakar, Adamu, Jabaka, Shehu, Tijani, Bello Idrith, Zeki, Akram M., Chiroma, Haruna, Usman, Mohammed Joda, Raji, Shakirat, Mahmud, Murni

    Published 2014
    “…Generally RSA algorithm gain a security support because of it’s frequently use in most applications where security of digital data is mostly a concern. …”
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  12. 12
    Mixed variable ant colony optimization technique for feature subset selection and model selection

    Mixed variable ant colony optimization technique for feature subset selection and model selection by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  13. 13
    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine

    Forest mapping in Peninsular Malaysia using Random Forest and Support Vector Machine Classifiers on Google Earth Engine by Farah Nuralissa Muhammad, Lam, Kuok Choy

    Published 2023
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  14. 14
    A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm.

    A recommender system approach for classifying user navigation patterns using longest common subsequence algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

    Published 2009
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  15. 15
    Age prediction on face features via multiple classifiers

    Age prediction on face features via multiple classifiers by Mohamad, F.S., Iqtait, M., Alsuhimat, F.

    Published 2018
    “…We were able to recognize that the accuracy of SVR algorithm is better than the accuracy of KNN and SVM classifiers.…”
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  16. 16
    Classification of basal stem rot disease in oil palm using dielectric spectroscopy

    Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

    Published 2018
    “…For feature selection algorithms, SVM-FS model gave the best classification accuracies compared to GA and RF; ranged from 81.82% to 88.64% with SVM and kNN as the best classifiers. …”
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  17. 17
    Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging

    Intelligent web proxy cache replacement algorithm based on adaptive weight ranking policy via dynamic aging by Olanrewaju, Rashidah Funke, Al-Qudah, Dua'a Mahmoud Mohammad, Azman, Amelia Wong, Yaacob, Mashkuri

    Published 2016
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  18. 18
    A Hybrid Approach For Web Search Result Clustering Based On Genetic Algorithm With K-means

    A Hybrid Approach For Web Search Result Clustering Based On Genetic Algorithm With K-means by Norita Md Norwawi, Bourair Al-attar, Ahmed J. Allami, Ali Thoulfikar A. Imeer, Yusor Fadhil Alasadi, Hawraa M. Kadhim

    Published 2024
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  19. 19
    Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction

    Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction by Abdul Muqtasid, Rushdi, Mohammad, Hossin, Norita, Norwawi

    Published 2025
    “…The Support Vector Machine (SVM) is well-regarded for its high classification accuracy, but its computational efficiency is often challenged by large datasets. …”
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  20. 20
    Analysing machine learning models to detect disaster events using social media

    Analysing machine learning models to detect disaster events using social media by Faris Azni Azlan, Mr.

    Published 2023
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