M
Masrah Azrifah Azmi Murad
Researcher at Universiti Putra Malaysia
Publications - 125
Citations - 1252
Masrah Azrifah Azmi Murad is an academic researcher from Universiti Putra Malaysia. The author has contributed to research in topics: Ontology (information science) & Software development process. The author has an hindex of 17, co-authored 116 publications receiving 1066 citations. Previous affiliations of Masrah Azrifah Azmi Murad include Information Technology University & Islamic Azad University.
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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
An experimental study of classification algorithms for crime prediction.
Rizwan Iqbal,Masrah Azrifah Azmi Murad,Aida Mustapha,Payam Hassany Shariat Panahy,Nasim. Khanahmadliravi +4 more
TL;DR: This paper compares the two different classification algorithms namely, Naive Bayesian and Decision Tree for predicting 'Crime Category' for different states in USA and showed that, Decision Tree algorithm out performed Naïve Bayesian algorithm and achieved 83.9519% accuracy.
Journal ArticleDOI
Quranic Verse Extraction base on Concepts using OWL-DL Ontology
TL;DR: This study proposes an ontology assisted semantic search system in the Qur’an domain that makes use of Quran ontology and various relationships and restrictions to enable the user to semantically search for verses related to their query in Al-Quran.
Proceedings ArticleDOI
Sentiment classification of customer reviews based on fuzzy logic
TL;DR: A fuzzy logic model is proposed to perform semantic classifications of customers review into the following sub-classes: very weak, weak, moderate, very strong and strong by combinations adjective, adverb and verb to increase holistic the accuracy of lexicon approach.