Search Results - (( web application ((use algorithm) OR (tree algorithm)) ) OR ( its application svm algorithm ))*
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A Proposed False Report Identification Algorithm for a Mobile Application in the IoT Environment
Published 2024Proceedings Paper -
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Named entity recognition using a new fuzzy support vector machine.
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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Article -
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Intelligent cooperative web caching policies for media objects based on decision tree supervised machine learning algorithm
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Conference or Workshop Item -
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An optimized attack tree model for security test case planning and generation
Published 2018“…By leveraging on the optimized attack tree algorithm used in this research work, the threat model produces efficient test plans from which adequate test cases are derived to ensure a secured web application is designed, implemented and deployed. …”
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Article -
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A Data Mining Approach to Construct Graduates Employability Model in Malaysia
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Car dealership web application
Published 2022“…The used car dealership web application was implemented with ASP.NET Core. …”
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Final Year Project / Dissertation / Thesis -
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An improved framework for content and link-based web spam detection: a combined approach
Published 2021“…The content-based web spam detection framework uses three proposed and two improved content-based algorithms for web spam detection. …”
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Thesis -
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Cyberbullying detection: a machine learning approach
Published 2022“…Machine learning is a hot topic and it is widely implemented in software, web application and more. Those algorithms are used in the classification or regression model to predict an input. …”
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Final Year Project / Dissertation / Thesis -
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
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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Article -
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Defect green coffee bean detection using image recognition and supervised learning
Published 2022“…Therefore, in this research project, the process will be conducted by using an image classifier with the model of a machine learning algorithm which the candidates comprise of Support Vector Machine, k-Nearest Neighbour and Decision Tree. k-nearest neighbour has the highest F1-score (0.51) than the other two algorithms (Support Vector Machine: 0.50, and Decision Tree: 0.48). …”
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Academic Exercise -
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Content-based recommender system for an academic social network / Vala Ali Rohani
Published 2014“…The algorithm exploits all interests and preferences in a hierarchy tree structure. …”
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Thesis -
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Comparative study of machine learning algorithms in data classification
Published 2025“…The results will help with real-world data mining applications of machine learning and be a useful guide for further study and practical applications.…”
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Final Year Project / Dissertation / Thesis -
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An Automated System For Classifying Conference Papers
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Final Year Project / Dissertation / Thesis -
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Context-Aware Recommender System based on machine learning in tourist mobile application / Nor Liza Saad … [et al.]
Published 2022“…Furthermore, data were collected simulated based on the mobile application prototype to be used for finding the suitable machine learning algorithms in the recommendation system module. …”
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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 -
19
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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