R
Rohana Mahmud
Researcher at University of Malaya
Publications - 32
Citations - 421
Rohana Mahmud is an academic researcher from University of Malaya. The author has contributed to research in topics: Malay & Learning environment. The author has an hindex of 11, co-authored 31 publications receiving 316 citations. Previous affiliations of Rohana Mahmud include University of Manchester & Information Technology University.
Papers
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Hadith data mining and classification: a comparative analysis
Mohammad Arshi Saloot,Norisma Idris,Rohana Mahmud,Salinah Jaafar,Dirk Thorleuchter,Abdullah Gani +5 more
TL;DR: All Hadith relevant methods and algorithms from the literature are discussed and analyzed in terms of functionality, simplicity, F-score and accuracy and it is revealed that neural networks classify the Hadith with 94 % accuracy.
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An application of case-based reasoning with machine learning for forensic autopsy
TL;DR: The experimental results reveal that the CBR method with the implementation of a learner is indeed a viable alternative method to the forensic methods with practical advantages, and the design and development of an Intelligent Forensic Autopsy Report System (I-AuReSys) basing on aCBR method along with the experimental results are presented.
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Towards knowledge modeling and manipulation technologies
Andrew Thomas Bimba,Norisma Idris,Ahmed Al-Hunaiyyan,Rohana Mahmud,Ahmed Abdelaziz,Suleman Khan,Victor Chang +6 more
TL;DR: A part of the findings from this survey is the high dependence of linguistic knowledge base, expert knowledge base and ontology on volatile expert knowledge, which is proposed for knowledge-based business management and other knowledge related applications.
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Adaptive feedback in computer-based learning environments
TL;DR: A distinct relationship between the characteristics of feedback, features of adaptive feedback, and computer-based learning models is revealed and open research questions in adaptive feedback implementations are identified.
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An architecture for Malay Tweet normalization
TL;DR: An approach to normalize the Malay Twitter messages based on corpus-driven analysis is proposed, which achieves higher accuracy by the normalization system, which is designed based on the features of Malay Tweets, compared to the SMT-like system.