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Support Vector Machines (SVM) in Test Extraction
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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Support Vector Machines (SVM) in Test Extraction
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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Entiment analysis of public perception on AI chatbots using Support Vector Machine (SVM) algoritm / Tuan Nur Azlina Tuan Ibrahim
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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Thesis -
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
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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Thesis -
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Improving Support Vector Machine Performance using Modified Similarity Distance Plotting-Data Reduction
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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Mixed variable ant colony optimization technique for feature subset selection and model selection
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Conference or Workshop Item -
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Support vector machine in precision agriculture: a review
Published 2021“…The applications of SVM in precision agriculture (PA) are compared by identifying its interactions with variables, comparing its model performance, highlighting its strengths and weaknesses, as well as suggestions for improvements. …”
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A technique of dispatching algorithms for web-server cluster
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Working Paper -
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Gender identification using support vector machines
Published 2023“…This thesis is introduces SVM theory application and its algorithmic implementations.…”
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Analysing machine learning models to detect disaster events using social media
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Age prediction on face features via multiple classifiers
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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Conference or Workshop Item -
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Classification of basal stem rot disease in oil palm using dielectric spectroscopy
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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Thesis -
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A comparative analysis of LSTM, SVM, and GSTANN models for enhancing solar power prediction
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Proceeding Paper -
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Locust- inspired meta-heuristic algorithm for optimising cloud computing performance
Published 2023“…This algorithm can also be used for task scheduling. The proposed algorithm efficiently maps and achieves the objective function for server consolidation, optimising energy consumption, VM migrations, and server utilisation. …”
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Thesis -
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Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes
Published 2013“…This research is to propose a new efficient DNS-based load balancing algorithms that can solve a sudden increase of demand for service requests when they are applied to a local Domain Name Service (DNS) server for Web based applications and selected services. …”
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