N
Nurfadhlina Mohd Sharef
Researcher at Universiti Putra Malaysia
Publications - 94
Citations - 892
Nurfadhlina Mohd Sharef is an academic researcher from Universiti Putra Malaysia. The author has contributed to research in topics: Collaborative filtering & Recommender system. The author has an hindex of 12, co-authored 84 publications receiving 606 citations. Previous affiliations of Nurfadhlina Mohd Sharef include Information Technology University & University of Bristol.
Papers
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Proceedings ArticleDOI
Detecting deceptive reviews using lexical and syntactic features
Somayeh Shojaee,Masrah Azrifah Azmi Murad,Azreen Azman,Nurfadhlina Mohd Sharef,Samaneh Nadali +4 more
TL;DR: Experiments on an existing hotel review corpus suggest that using stylometric features is a promising approach for detecting deceptive opinions.
Journal ArticleDOI
An Analysis of Ontology Engineering Methodologies: A Literature Review
TL;DR: A critical analysis and comparison of several ontology engineering methodologies showed that there is no completely mature methodology and this research may act as a preliminary guide to come with a state of art ontology Engineering methodology, bridging up the existing gaps and shortfalls.
Journal ArticleDOI
Preference learning for eco-friendly hotels recommendation: A multi-criteria collaborative filtering approach
Mehrbakhsh Nilashi,Ali Ahani,Ali Ahani,Mohammad Dalvi Esfahani,Elaheh Yadegaridehkordi,Sarminah Samad,Othman Ibrahim,Nurfadhlina Mohd Sharef,Elnaz Akbari +8 more
TL;DR: A new soft computing method is developed with the aid of machine learning techniques in order to find the best matching eco-friendly hotels based on the several quality factors in TripAdvisor to improve the scalability of prediction from the large number of users' ratings.
Journal ArticleDOI
Determining Importance of Many-Objective Optimisation Competitive Algorithms Evaluation Criteria Based on a Novel Fuzzy-Weighted Zero-Inconsistency Method
R. T. Mohammed,A. A. Zaidan,Razali Yaakob,Nurfadhlina Mohd Sharef,R. H. Abdullah,B. B. Zaidan,Osamah Shihab Albahri,Karrar Hameed Abdulkareem +7 more
TL;DR: A new method, called a Novel Fuzzy-Weighted Zero-Inconsistency (FWZIC) Method which can determine the weight coefficients of criteria with zero consistency is proposed which is applied to the evaluation criteria of MaOO competitive algorithms.
Journal ArticleDOI
Sequence to Sequence Model Performance for Education Chatbot
Kulothunkan Palasundram,Nurfadhlina Mohd Sharef,Nurul Amelina Nasharuddin,Khairul Azhar Kasmiran,Azreen Azman +4 more
TL;DR: Intelli-gence based chatbots can learn and become smarter overtime and is more scalable and has become the popular choice for chatbot researchers recently, while Recurrent Neural Network based Sequence-to-sequence (Seq2Seq) model is still in infancy and has not been applied widely in educational chatbot development.