Search Results - (( web application new algorithm ) OR ( _ application ((based algorithm) OR (bayes algorithm)) ))*

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    Efficient DNS based Load Balancing for Bursty Web Application Traffic by Chin, Mei Lu, Chong, Eng Tan, Mohamad Imran, Bin Bandan

    Published 2012
    “…This research proposes a new efficient load balancing algorithm which applies to the local Domain Name Service (DNS) server for web based applications and services to ease the sudden increase in demand for the services. …”
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    Article
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    Content-based recommender system for an academic social network / Vala Ali Rohani by Vala Ali, Rohani

    Published 2014
    “…The rapid growth of Web 2.0 applications, such as blogs and social networks creates rich online information and provides various new sources of knowledge. …”
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    Thesis
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    Mobile banking Trojan detection using Naive Bayes / Anis Athirah Masmuhallim by Masmuhallim, Anis Athirah

    Published 2024
    “…The objectives of this project are to study the requirement of the Naive Bayes algorithm in Mobile Banking Trojan detection, to develop a webbased detection system for Mobile Banking Trojan using Naive Bayes, and to evaluate the performance and accuracy of the Naive Bayes algorithm in the Mobile Banking Trojan detection. …”
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    Thesis
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    Fake news detection: A machine learning approach by Yeoh, Dennis Guan Lee

    Published 2021
    “…These models were evaluated in order to pick one to be deployed to the web application. The final model chosen to be deployed was a model trained using a Multinomial Naïve Bayes algorithm.…”
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    Final Year Project / Dissertation / Thesis
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    Adaptive System State Based Load Balancing For Web Application Server Cluster Of Heterogeneous Performance Nodes by Lu, Chin Mei

    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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    Improving malicious detection rate for Facebook application in OSN platform by Angamuthu, Laavanya

    Published 2018
    “…Therefore, to identify malicious apps, we ask the question: given a Facebook application, can we determine if it is malicious? Our key contribution in this part is in developing malware detection in Facebook third party application by using Naïve Bayes algorithm technique .We identify a set of features that help us distinguish malicious apps from benign ones. …”
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    Thesis