K
Kasturi Dewi Varathan
Researcher at University of Malaya
Publications - 38
Citations - 1245
Kasturi Dewi Varathan is an academic researcher from University of Malaya. The author has contributed to research in topics: Computer science & Knowledge representation and reasoning. The author has an hindex of 10, co-authored 32 publications receiving 779 citations. Previous affiliations of Kasturi Dewi Varathan include Information Technology University & National University of Malaysia.
Papers
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Identification of significant features and data mining techniques in predicting heart disease
TL;DR: Experimental results show that the heart disease prediction model developed using the identified significant features and the best-performing data mining technique (i.e. Vote) achieves an accuracy of 87.4% in heart disease Prediction.
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Cybercrime detection in online communications
TL;DR: A set of unique features derived from Twitter; network, activity, user, and tweet content, based on these feature, a supervised machine learning solution for detecting cyberbullying in the Twitter network is developed.
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Using online social networks to track a pandemic: A systematic review.
Mohammed Ali Al-Garadi,Muhammad Sadiq Khan,Kasturi Dewi Varathan,Ghulam Mujtaba,Abdelkodose M. Al-Kabsi +4 more
TL;DR: OSN data contain significant information that can be used to track a pandemic, but it can offer complementary data that can work best when integrated with traditional data.
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Malicious accounts
TL;DR: A comprehensive review of related studies that deal with detection of malicious accounts on social networking sites focusing on four main categories, which include detection of spam accounts, fake accounts, compromised accounts, and phishing.
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Analysis of Online Social Network Connections for Identification of Influential Users: Survey and Open Research Issues
Mohammed Ali Al-Garadi,Kasturi Dewi Varathan,Sri Devi Ravana,Ejaz Ahmed,Ghulam Mujtaba,Muhammad Usman Shahid Khan,Samee U. Khan +6 more
TL;DR: A detailed survey of influential users’ identification algorithms and their performance evaluation approaches in OSNs is presented, covering recent techniques, applications, and open research issues on analysis of OSN connections for identification of influential Users.